{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " 房屋的价格取决于很多因素，就拿美国的房屋来说(咱中国情况特殊)房屋的价格取决于所在的区域,房屋的面积,卧室的数量，卫生间的数量，院子的大小,地下室的面积,车库的数量等等很多变量。在众多的变量中房屋所在区域应该对房屋价格影响最大,但是相同区域的房价,也会因为其他变量的不同而有所差异。今天我们就拿kaggle中的一个案例来分析一下房屋价格和其他变量之间存在的关系,并通过可视化的方式来呈现出这种关系,接着我们要使用ElasticNet和xgboost来创建几个回归模型对价格进行预测,最后我们要评估这些模型的性能,并从中找出表现最好的模型。通过对这个案例数据的分析,可以让大家掌握一些基本的统计学的基础知识如正太分布,均值、标准差、理论分位图(QQ图)、相关系数等知识,这对应想从事数据分析工作的朋友来说有很大的帮助。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDA(探索性数据分析)\n",
    "你可以从这里下载我们的数据，然后加载我们所需要的一些包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "from scipy import stats\n",
    "from scipy.stats import norm, skew\n",
    "from sklearn import preprocessing\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import ElasticNetCV, ElasticNet\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from xgboost import XGBRegressor, plot_importance \n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns\n",
    "def ignore_warn(*args, **kwargs):\n",
    "    pass\n",
    "import warnings\n",
    "warnings.warn = ignore_warn\n",
    "pd.set_option('display.float_format', lambda x: '{:.3f}'.format(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果有发现某些包没有安装,那请在jupyter notebook中使用 !pip install xxx 进行安装。加载完所需要的包以后，我们导入我们的数据:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1460, 81)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.000</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.000</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.000</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.000</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.000</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL       65.000     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL       80.000     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL       68.000    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL       60.000     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL       84.000    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities    ...     PoolArea PoolQC Fence MiscFeature MiscVal  \\\n",
       "0         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "1         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "2         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "3         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "4         Lvl    AllPub    ...            0    NaN   NaN         NaN       0   \n",
       "\n",
       "  MoSold YrSold  SaleType  SaleCondition  SalePrice  \n",
       "0      2   2008        WD         Normal     208500  \n",
       "1      5   2007        WD         Normal     181500  \n",
       "2      9   2008        WD         Normal     223500  \n",
       "3      2   2006        WD        Abnorml     140000  \n",
       "4     12   2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 81 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#加载数据\n",
    "df = pd.read_csv('./data/house/train.csv')\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "总共有1460条记录，共有81列,其中SalePrice是我们的目标变量，除去SalePrice和Id这两列以外,其余79个变量都是我们的特征变量,这些特征变量的含义在这我就不一一说明了(因为实在太多),大家可以查看kaggle中的Data Description。接下来我们要做数据清洗的工作,因为有很多字段有空值,我们必须要清洗掉这些数据,首先我们要查询一下数据中的空值情况:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PoolQC         0.995\n",
       "MiscFeature    0.963\n",
       "Alley          0.938\n",
       "Fence          0.808\n",
       "FireplaceQu    0.473\n",
       "LotFrontage    0.177\n",
       "GarageCond     0.055\n",
       "GarageType     0.055\n",
       "GarageYrBlt    0.055\n",
       "GarageFinish   0.055\n",
       "GarageQual     0.055\n",
       "BsmtExposure   0.026\n",
       "BsmtFinType2   0.026\n",
       "BsmtFinType1   0.025\n",
       "BsmtCond       0.025\n",
       "BsmtQual       0.025\n",
       "MasVnrArea     0.005\n",
       "MasVnrType     0.005\n",
       "Electrical     0.001\n",
       "Utilities      0.000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看变量包含空值的比例\n",
    "(df.isnull().sum() / len(df)).sort_values(ascending=False)[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们查看了前20个包含空值最多的变量(字段)，其中PoolQC、MiscFeature、Alley、Fence这4个变量所包含空值的比例都在90%和80%以上,它们包含了大量的空值。所以我们要删除这些变量,同时为了便于后续的分析,我们还要同时删除Id字段。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#删除包含空值最多的4个变量和Id\n",
    "df.drop(['PoolQC', 'MiscFeature', 'Alley', 'Fence', 'Id'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 目标变量\n",
    "SalePrice是我们的目标变量,也是最后我们要预测的变量,所以我们要对它进行深入分析,首先我们要查看SalePrice的数据分布情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\ProgramData\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " mu = 180921.20 and sigma = 79415.29\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rR0T7DwVuc/c17v428BZwQPT3lrvPdfdPgduAoTnOISLSrNGj4Ywzsk8/k6mgQ2fu8PTT4bpLnz7wne+EpHPVVfDuu3D77TB4cJhqukjEKX1e7e6rzQwz29LdXzOz3WIe/xrgv4Cto+2ewIqM0umFQN/oeV9gAYC7rzOzD6P9+wLPZBwz8z0LmrQfmOMcGzGzUcAogKpKXBRcRIDWXZ8paNXZ+++Hk9fVwauvQrducOqpMHJkqCyz5uq5ikOcZLPQzHoA9wKPmNlyYFGuN5nZMcB77j7TzP4t3dzMrp7jtZbam+uVZdt/00b38YTlE6iurm7dvD0iUvJSKRgxAj79NN7+nTrBpEl5TjSNjeEif20tTJ0aSpYPPjhsn3wybL117mMUgThLDJwQPf2ZmT0ObAs8FOPYhwLHmdm3CBN4bkPo6fQws05Rz6MfGxLXQqA/Ibl1is6zLKM9LfM9zbUvzXIOEZFWJxkInYa8Jpp580LJ8sSJoWS5Vy/43vfC0FnCN2AmocVrNmb2ZzMbHq1jA4C7P+nuU6NrJFm5+6Xu3s/dBxIu8D/m7sOBx4GTot3OBu6Lnk+Ntolef8zDLKFTgVOjarWdgV2BZ4HngF2jyrMtonNMjd7T0jlEpMKlr820JtF06hRuuE880axZA1OmwNFHwy67wBVXhMRyxx3hWsxVV5VkooHsPZvxhB/wa8zsMeBW4IE4iSaHi4HbzOx/gBeAuqi9DrjZzN4i9GhOBXD32WZ2OzCHMF3OBe7eCGBmFxKq4zoCE9x9do5ziEgFO/JImD69de/ZaqswYpVoopk1K1yHqa8Ps3xWVcFll4U7SsvkenLOJQbMrAtwHOHH/2DgAeBWd38k+fDyR0sMiJS31iYas4R7MytXwm23hUz27LPQuTOccEIYJjviiKKqJMsm7hIDca7ZfAJMAaaY2V6EUuKzCb0JEZGil0oVSaJJlyzX1YXhsoaGMGXM1VeHsb1evdr5hMUjzhIDOwInE3o2fYA7gBizBYmIFIeRI+Pvm8iw2XvvbShZfu21cOfo6aeHwA44oKhLlttLtlmfvwOcBuwG3A38l7s/la/ARETaw+jRsHp17v3aPck0NsLDD28oWV63Dg45JCSck08OCaeCZOvZHAL8EnjU3dfnKR4RkXaTSsW7WfOII8Ls++3i7bc3lCwvXBiGxsaMCbXWJVpJ1h6yzfqsoTIRKVmpVLgMkku7LHa2ejXce2/otTz6aBgWGzwYrrkGjj0WttBcwHFmEBARKSlxp5+pr9/MYbNZs8IwWX09LFsWJrz8+c/hnHPKpmS5vSjZiEhZ2XPPsNJxLlts0cZE89FHG0qWn3suHCizZLlDrJVbKk6cZaGbpWWhRaTY9O0Li2JOTjVhQisO7A5PPRWGyW6/PZQsf+lLYZjsjDPC6peSVdxloasI68IY0AN4B9BKniJSNFqTaI44ImavZsmSDSXLr78eKsiGDw8ly/vvXxEly+0l57LQZvYHwpxjD0Tb3wSOzE94IiLZtXZmgEGDclSeNTaGVS1ra+FPfwoly4ceChdfDMOGVVzJcnuJc81mf3c/L73h7g+a2RUJxiQiklNr1qBJ22knmD27hRfffjuMrU2cGCa97N0bvv/9ULK8xx6bHW+li5NslprZT4B6wrDaGcAHiUYlItKMtiSYtEGDmkk0q1fDPfeEYbLp08PF/cGD4brr4JhjVLLcjuIkm9OAy4B7CMnmL1GbiEjexK0ya84m99K8/PKGkuXly2HgQLj88lCy3L9/C0eRzRFnIs5lwBgz6+7uH+chJhGRjWxOovnsXpoPP9xQsjxjRui1nHhiKFk+/HCVLCcs57drZoeY2RzCejKY2VfMbHPvtxURiWWzEs3NzvCqv4YeS58+cN55YYGya68NpWu33hoqDJRoEhdnGO1qYDBhxUzc/SUz+3qiUYmI0PZEs1PHJdw/bDL7XFEHb7wBW28NZ54ZSparq1WyXACxZhBw9wW28T+cxmTCEREJjjyydYmmI+v4drdpTDmqFu6/H25bB1/9Klx6aShZ7tYt90EkMXGSzQIzOwRwM9sCuAh4NdmwRKSStaZHszNzGcEELuw2kR6rFsHTO8APfhBKlnffPdlAJbY4yeY84FqgL7AQeBi4IMmgRKRybbcdrFiRfZ8tWc2J3M1FXes4qOGxcM3lG0Ng5PWhZLlz5/wEK7FlTTZm1hE4092TWoVbROQzXbvCJ5+0/PpevMRIahlOiu1ZDjvuDCOuCAUA/frlLU5pvazJxt0bzWwooUhARCQR2YbNtuFDTuNWRlJLNTNZzZY82OVETvhTDRx2mCrJSkScYbSnzOx6YAqwKt3o7s8nFpWIVISWh8ycr/FXaqhjGHfQlU94ib34Htdx/zbDefvDrJPSSxGKk2wOiR4vz2hz4PD2D0dEKkFLPZkd+RdnM5kRTGA33uBDtuEmzqKWkcxkP3r0MJYvz3+8svnizCBwWD4CEZHy19xSzR1Zxzd5kBrqOIb76UQjf+FrXMmPuZOTaCCULO+0U5gfU0pTzmRjZjsCVwI7ufs3zWwQcLC71yUenYiUjaa9mV34JyOYwLlMZCcWs4QduIofMYERvMFuG71Xiab0xbmyNgmYBuwUbb8BfD+pgESkvKRS4Yb9OXNgKz7hdFJM53D+yRe4hF/yPPtyPPfQj4Vcwq82STSDBinRlIM412x6ufvtZnYpgLuvMzPNICAiOaVLmffmBWqoYzgptmMF/2QXxvI/TOIcFtG32feawc03x1xRU4penGSzysx6EooCMLODgA8TjUpESlrfvrBq0QrOjkqW9+N5VrMld/FtahnJk3wDzzKwssmSAFLy4iSbHxIm4fy8mT0F9AZOSjQqESlN7nyjw1/4RVSy3IXVvMhXuJDfcQuns5yWS5Y7d4ZPP81jrJJXcarRnjezbwC7AQa87u5rE49MRErH4sUweTJvXDqBJ3mTD9mGSZxDLSN5nn0JPx0tU0+m/LWYbMzsxBZe+qKZ4e53JxSTiJSCdevgwQe5//hahqz/M51oZDFf5wr+m7v4Np/QNdZh3BOOU4pCtp7NsdHjDoQbOx+Ltg8DngCUbEQq0VtvwYQJLP7FJPqwmGp25Df8BxMYwZt8MfZhBg2C2bMTjFOKSovJxt3PBTCz+4FB7r442u4D3JCf8ESkKHzyCdx1F0vG1bLja0/SSAee49+po4YH+BbriD/Lcpcu0NCQYKxSlOIUCAxMJ5rIEmjF/76ISOl6/nmoq6OhNkXXTz9kJZ/nGq5kMmez+LNb7+Krr1cpc6WKk2yeMLNpwK2E8udTgccTjUpECmf5crjlFqirgxdeYDVbcjcnUUdNzpLllmjITOJUo11oZicAX4+axrv7PcmGJSJ55Q5PPgm1tXDXXbB6Ney9NxdwPbdwOivYrs2HVm9GIN7iadPc/UhACUak3CxaBJMnh17MP/8J227LpA4juI4aXnhx3806tO6bkUxZ+8Pu3gg0mNm2eYpHRJK2di3cdx8cdxxUVcGPfwz9+vHLQTfR9cNFnNtwAy/Q9kRTXx86Sko0kinONZvVwCwze4SNF0+7KLGoRKT9vflm6MFMngz/+hd87nPwn/8JI0ZgX9x1sw+v4TLJJs6Vvj8D/w38BZiZ8ZeVmfU3s8fN7FUzm21mY6L27c3sETN7M3rcLmo3M7vOzN4ys5fNbN+MY50d7f+mmZ2d0b6fmc2K3nOdmVm2c4hUnIaGMJvlN74BX/wi/OY3sP/+cN99XDh0AfbLX2xWouncOfRi3JVoJLs4yWYKIbnMAKa4+2R3nxzjfeuAH7n7HsBBwAXRWjiXANPdfVdgerQN8E1g1+hvFHAjhMQBXAYcCBwAXJaRPG6M9k2/b0jU3tI5RCrD88/D6NHQpw+cdVaYo//KK+Gddxjdbyo29Dhu+L84AxvN69JFQ2XSOi0mGzPrZGa/BhYCk4F6YIGZ/drMct7B5e6L3f356PlK4FWgLzA0Oh7R4/HR86HATR48A/SIbiAdDDzi7svcfTnwCDAkem0bd/+7uztwU5NjNXcOkfK1fDlcfz3ssw/stx9MnBiuyzzxBLz5JqmqS7G+O3HjjZt3mvp63ZQprZftf23+F9ga2DlKFpjZNsBvor8xcU9iZgOBfYB/ADumbxJ198VmtkO0W19gQcbbFkZt2doXNtNOlnM0jWsUoWdEVVVV3I8jUjzWr9+4ZHnNGth3X7jhBjj9dLbbuQcr6tvvdLouI22VLdkcA3wx6jUA4O4fmdn5wGvETDZm1h24C/h+9P4Wd22mzdvQHpu7jwfGA1RXV2s6QCkdixbBpEnhgv/cubDttjByJNTUwD770LEjrL+gfU6lJZmlPWS7ZuOZiSajsZGYP+rRcNtdQCpjlugl0RBYep6196L2hUD/jLf3AxblaO/XTHu2c4iUrrVr4d574dhjoX9/GDs2lC7X19Plw8XYDddj++6DWejwbK70xX8lGmkP2ZLNHDM7q2mjmZ1B6NlkFVWG1QGvuvtvM16aCqQrys4G7stoPyuqSjsI+DAaCpsGHG1m20WFAUcTbjRdDKw0s4Oic53V5FjNnUOk9LzxBlx8cUgwJ5wAM2fyu64X8wXexJ54HDtjOKvp0q6nrK/XxX9pX9mG0S4A7jazEYRqNAf2B7oAJ8Q49qHAmYR7dF6M2n4M/BK43cxqgHeAYdFrDwDfAt4CGoBzAdx9mZldATwX7Xe5uy+Lnp8PTIpiejD6I8s5REpDQwPceWe4FvPXv0LHjrzU/xh+Qg0PLv4mjbFukWs9rS0jSbFmRso23sHscGBPwjWS2e4+PR+B5Vt1dbXPmDGj0GFIJXOHmTPDdZhbboGPPoIvfIFxS0Zy/cqz+Bd9Ejlthw7Q2JjIoaUCmNlMd6/OtV+ciTgfY8PCaSLS3pYtg1QqJJmXXoIuXXhk25O44qOR/PWtr5FrSeXNoZ6M5EsyfXERyW79+nD/S20t3H03rFnD/N778Ut+z62fnMaHn/RI5LQ9eoTbcUTyTclGJJ/efTeULE+YAHPnspwe1PMd6qjhpff3Tuy0RxwBjz6a2OFFclKyEUna2rVw//1hmOzBB2H9eh7jMGq5gns4od0ryQDOPx9+//t2P6xImynZiCTl9dehro6Prp/MNp+8x7vsxCQuYQIjmMvn2/VUWjtGip2SjUh7WrWKp394J43ja/kaf2MdHZnOsdRRw0MMafeSZV3gl1KhZCOyGTp2hPXrnWpmUEMdp3MLh7CSN9iV/+JX3MRZLOFz7XpO9WKkFCnZiMTUt2+YkixtO5ZxAfXUUMdXeJkGunAHw6hlJH/jq7R3ybJ6MVLKlGxEmrHddrBixabtxnoO43FGUssJ3MNWrOE5qjmPG7mV0/iI9l1BXQlGyoWSjVS8lhJLpr4s5BwmMYIJ7MLbLGM7xjOKOmp4ma+0WyyaYVnKlZKNVJw4yQWgM59yDPdTQx1DeIiOrGc6hzOWcdzDCaxhq3aJRzdaSiVQspGytueeMGdO696zG69RQx1ncRM7EkqWf8GlTGAEb7NLu8Sl4TGpNEo2UlaaXsSPqyurGMYdjKSWr/IUa+nEn6KS5WkM3uySZSUXqXTZ1rMRKUqpFJg1/9e6ROPsz7P8ge+ymD5M4lx68z7/ya/px0K+zd08wL+3KtGcf35ILE3/RCqdejZSEuJeZ4ljez7gjKhkeS9m0UAXbudkahnJUxxK3JJlXcwXiU/JRopSW4fDWmKs53Ae+6xkeUs+5Vn257v8gds4NWfJsiayFNk8SjZSNEaPhhtvbN9j9mPBZyXLOzOPZWzHHziPOmqYxV7NvkeJRaT9KdlIwbSlUiyOznzKsfzps5LlDjiPcgSX8gvu5fhNSpY1Q7JI8pRsJHGpFIwYkfx8Xrvz6mclyzvwPgvpyzjGMpFzPytZVq9FpDCUbKTd5CupZOrGx5zM7dRQx6E8zVo6MZXjqKOGhxnM5PqOzB2ev3hEpHlKNpJTKgXf/S6sWlXoSNKcA3iWGuo4jVvZmo9ht91g5P/S+cwz+faOO/LtQocoIhtRspFmjR4Nf/hDcd0j0pOlnEE93+1Uxx7rXoGuXeHkk2HkSDjkkHCjjYgUJSUb2UghhsKyMdZzyvaPcuuRdXDAc1jwAAAN3klEQVTvvSGwfQ+Amv+DU0+FbbYpdIgiEoOSTQVLpWDMGPjgg0JHsql+LOD3+0/k2PcmwPz58Oj2oWyspga+/OVChyciraRkU4GK7xpMVCX2wKcwdSrU1cG0afCcw5FHwq9+BUOHwlbtM8uyiOSfkk0ZK9aeyyb3tcyZExJM35tg6VLo1w9+8hM491zYeeeCxSki7UfJpgykUjB2bBht6tgRGhvDtfJCXtzv3j0UGAxvqez444/h9tuhthb+/nfo1Cn0XkaOhKOOCh9ERMqGkk0JykwuTZNKY2N4TCLRdOgQht/afLe9O/zjH6EXc9ttIeHsvjv85jdw5pmwww7tGq+IFA8lmxKTSsGoUdDQELaT7r3k7KHEsXQp3HxzSDKzZ4eS5VNPDRf7Dz5YJcsiFUDJpsSMHbsh0SSpZ0+49trNSDLr14d5YWprQ8ny2rVw4IHwxz/CKafA1lu3a7wiUty0eFoRSKVg4MAwTDVwYNhu2jZ6dHicP7/9z9+9O9TXb7zY19KlbUw077wDP/95uLA/eDBMnw4XXACzZsEzz4RrMko0IpXH3fXnzn777eetVV/vPmCAu1l4rK9v/f719e5du268rmPnzu5bbNHceo/t+9ezZ+6YY1m92v32292PPjp8OLPwfMqU8JqIlC1ghsf4jdUwWhs1vXYyf37YhuZ7BC3t36XLpsNia9e2Pa4OHcIIVroqbcAAGDduM6+5tGT27HAd5qabQn11//7w05+GkuUBAxI4oYiUKvNimvyqgKqrq33GjBmx929pSGvAAJg3L/7+mysvSSXTypUwZUpIMs88A507h5LlmhqVLItUIDOb6e7VufZTz6aN3nmnfdo3R0uJrd25h8RSWxsSzapVMGgQXHVVKFnu3TsPQYhIKVOyaaOqquZ7KlVVrdu/Z0/45JONh9I6dw7VwNkmw+zaNfRkEvX++6FkubYWXn0VunXbULJ80EEqWRaR2FSN1kbjxoUf/EzZEkBL+197LYwfH3opZuFx4kSYMGHjtvPP33h7/PiEhswaG+Ghh2DYMOjbF370I9h221CyvHhxSDy6N0ZEWkk9mzZK/9CPHRuGyKqqsl8zybV/c+9L/PpLpnnzQpabOBEWLAhdrgsvDL2YPffMYyAiUo5UIBBpbYFAWVizBu67L/RWHn00tB11VLgX5rjjYMstCxufiBS9ii8QMLMhwLVAR6DW3X9Z4JCKxyuvhGqym28OJctVVSpZFpFElWWyMbOOwA3AUcBC4Dkzm+rucwobWQGtXBkmv6yrC5Nhdu4Mxx8fejFHHKGSZRFJVFkmG+AA4C13nwtgZrcBQ4HKSjbuYfr+2townf+qVeH6y29/C2ecoZJlEcmbck02fYEFGdsLgQOb7mRmo4BRAFUt1SyXovfe21Cy/NproWT5tNPCxf4DD1QlmYjkXbkmm+Z+TTephHD38cB4CAUCSQeVqMZGePjhMEx2332wbl0oUa6rg5NPDrNtiogUSLkmm4VA/4ztfsCiAsWSrHnzwk05EyfCwoXQqxdcdFHoxQwaVOjoRESA8k02zwG7mtnOwLvAqcDphQ2pHa1ZE9aIqa0NU/hDmM7/6qtDyfIWWxQ2PhGRJsoy2bj7OjO7EJhGKH2e4O6zCxzW5ps1a0PJ8rJloUz5Zz+Dc85peZ4cEZEiUJbJBsDdHwAeKHQcm+2jjzaULD/7bOi1ZJYsd9CMQyJS/Mo22ZQ0d3j66Q0lyw0NoWT56qtDyXKvXoWOUESkVZRsisl774WFyOrqQsly9+5hgrSaGjjgAJUsi0jJUrIptMZGmDYtJJipU0PJ8iGHhAqzYcNUsiwiZUHJplDefjsklEmTQsly794wZkzoxeyxR6GjExFpV0o2+bR69cYly2YwZAhccw0ce6xKlkWkbCnZ5MPLL28oWV6+PJQsX355KFnu3z/n20VESp2STVI++ghuvTUkmeeeC72WE04IJcuHH66SZRGpKEo27ckdnnoqDJPdcUcoWf7Sl8Iw2RlnhNUvRUQqkJJNe1iyZEPJ8uuvw9Zbh+RSUwP776+SZRGpeEo2m+u880KSWbcODj0ULrkklCx361boyEREioaSzebaeWf4/vdDL2b33QsdjYhIUVKy2VwXX1zoCEREip5KokREJHFKNiIikjglGxERSZySjYiIJE7JRkREEqdkIyIiiVOyERGRxCnZiIhI4szdCx1DUTCz94H5eT5tL2Bpns/ZHhR3finu/FLcrTPA3Xvn2knJpoDMbIa7Vxc6jtZS3PmluPNLcSdDw2giIpI4JRsREUmckk1hjS90AG2kuPNLceeX4k6ArtmIiEji1LMREZHEKdmIiEjilGwKzMyuMLOXzexFM3vYzHYqdExxmNn/mtlrUez3mFmPQscUh5kNM7PZZrbezIq2TDTNzIaY2etm9paZXVLoeOIwswlm9p6ZvVLoWFrDzPqb2eNm9mr078iYQscUh5ltZWbPmtlLUdw/L3RMzdE1mwIzs23c/aPo+UXAIHc/r8Bh5WRmRwOPufs6M/sVgLsX/bKlZrYHsB74P+A/3H1GgUNqkZl1BN4AjgIWAs8Bp7n7nIIGloOZfR34GLjJ3b9U6HjiMrM+QB93f97MtgZmAseXwPdtQDd3/9jMOgN/A8a4+zMFDm0j6tkUWDrRRLoBJZH93f1hd18XbT4D9CtkPHG5+6vu/nqh44jpAOAtd5/r7p8CtwFDCxxTTu7+F2BZoeNoLXdf7O7PR89XAq8CfQsbVW4efBxtdo7+iu53RMmmCJjZODNbAAwHflroeNpgBPBgoYMoQ32BBRnbCymBH79yYGYDgX2AfxQ2knjMrKOZvQi8Bzzi7kUXt5JNHpjZo2b2SjN/QwHcfay79wdSwIWFjXaDXHFH+4wF1hFiLwpx4i4R1kxb0f0fa7kxs+7AXcD3m4w8FC13b3T3vQkjDAeYWdENX3YqdACVwN2PjLnrLcCfgcsSDCe2XHGb2dnAMcARXkQX/1rxfRe7hUD/jO1+wKICxVIRomsedwEpd7+70PG0lruvMLMngCFAURVoqGdTYGa2a8bmccBrhYqlNcxsCHAxcJy7NxQ6njL1HLCrme1sZlsApwJTCxxT2YoutNcBr7r7bwsdT1xm1jtdDWpmXYAjKcLfEVWjFZiZ3QXsRqiQmg+c5+7vFjaq3MzsLWBL4IOo6ZkSqaI7Afgd0BtYAbzo7oMLG1XLzOxbwDVAR2CCu48rcEg5mdmtwL8RprxfAlzm7nUFDSoGM/sq8FdgFuG/R4Afu/sDhYsqNzPbC5hM+HekA3C7u19e2Kg2pWQjIiKJ0zCaiIgkTslGREQSp2QjIiKJU7IREZHEKdmIiEjilGykrJhZz2gG7RfN7F9m9m70fIWZ5XVCRTPbOypdTm8f19aZm81snpn1ar/oWnXuczJnIzezWjMbVOi4pLQo2UhZcfcP3H3vaOqOPwBXR8/3ZsO9E+3GzLLNwrE38Fmycfep7v7L9o4hD84BPks27j6y2GdCluKjZCOVpKOZ/TFa8+Ph6G5rzOzzZvaQmc00s7+a2e5R+wAzmx6t2TPdzKqi9klm9lszexz4lZl1i9Zwec7MXjCzodEd/5cDp0Q9q1OiHsL10TF2tLAO0EvR3yFR+71RHLPNbFSuD2Rm55rZG2b2ZPTZ0sefZGYnZez3cfTYPfosz5vZrPR8cWY20MI6Lht9P9ExqoFU9Dm6mNkT1sxaQGZ2hoV1VV40s/+zMDlkxyiWV6Lz/WAz/vlJCVOykUqyK3CDu+9JmD3g21H7eOB77r4f8B/A76P26wlrsuxFmGj0uoxjfRE40t1/BIwlrO2zP3AY8L+Ead5/CkyJelpTmsRyHfCku38F2BeYHbWPiOKoBi4ys54tfRgL66/8HDiUsObNoBjfwWrgBHffN4r1qmialma/H3e/E5gBDI8+xyctxLIHcApwaNSTbCTMYr430Nfdv+TuXwYmxohRypAm4pRK8ra7vxg9nwkMjGb4PQS4Y8NvLltGjwcDJ0bPbwZ+nXGsO9y9MXp+NHCcmf1HtL0VUJUjlsOBsyDM2At8GLVfFE2pA2ESzl3ZMCVQUwcCT7j7+wBmNoWQBLMx4EoLC5ytJyxZsGP02ibfT45jZToC2A94LvoeuxCmu/8TsIuZ/Y4wyezDrTimlBElG6kkazKeNxJ+EDsAK6L/G88lc26nVRnPjdAL2GhRNjM7sDXBmdm/ESZRPNjdG6LZe7dqRUyZ1hGNXEQ9ly2i9uGEeeH2c/e1ZjYv4xzNfT+xwwcmu/ulm7xg9hVgMHABcDJh/SOpMBpGk4oWrVfytpkNg/DDHP04AjxNmGkZwo/031o4zDTge+nhKDPbJ2pfCWzdwnumA+dH+3c0s22AbYHlUaLZHTgoR/j/AP4tqsDrDAzLeG0eoacBYXXPztHzbYH3okRzGDAgxzlyfY7Mz3OSme0Qfabto2tevYAO7n4X8N+EIUOpQEo2IiGR1JjZS4RrJ+lF1i4CzjWzl4EzgTEtvP8Kwo/5y2b2SrQN8DgwKF0g0OQ9Y4DDzGwWYchqT+AhoFN0visIy223yN0XAz8D/g48Cjyf8fIfgW+Y2bOE4bZ0TywFVJvZjOhzx5mKfhLwh3SBQAuxzAF+Ajwcxf8I0IcwTPeEhVUkJwGb9HykMmjWZ5EyYWbnANXuXjSrvYqkqWcjIiKJU89GREQSp56NiIgkTslGREQSp2QjIiKJU7IREZHEKdmIiEji/h+FZQ3MVZ1U0AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['SalePrice'] , fit=norm);\n",
    "\n",
    "#得到均值和标准差\n",
    "(mu, sigma) = norm.fit(df['SalePrice'])\n",
    "print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
    "\n",
    "\n",
    "plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
    "            loc='best')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Sale Price distribution')\n",
    "\n",
    "#画QQ图\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(df['SalePrice'], plot=plt)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上面那个图是SalePrice的数据分布图(直方图),同时我们用正太分布对它进行拟合,并得到了两个参数均值(μ)和标准差(σ),用肉眼就能看出SalePrice出现右偏(右侧有长尾),严重偏离正态分布。底下的是QQ图(理论分位数图),它的主要作用是判断样本是否近似于某种类型的分布，如果图中的蓝色点偏离了红线,说明数据不服从正太分布(如果蓝点紧紧围绕红线,那就是服从正态分布)。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 纠偏\n",
    "当发现SalePrice呈现偏斜的分布以后,我们要对它进行纠偏,我们要数据进行对数化处理,这类似与机器学习中的归一化处理的概念,是一种数据标准化处理的方法。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " mu = 12.02 and sigma = 0.40\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(np.log1p(df['SalePrice']) , fit=norm);\n",
    "\n",
    "# 纠偏,对数化处理。\n",
    "(mu, sigma) = norm.fit(np.log1p(df['SalePrice']))\n",
    "print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
    "\n",
    "#纠偏后再化分布图\n",
    "plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
    "            loc='best')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('log(Sale Price+1) distribution')\n",
    "\n",
    "#画QQ图\n",
    "fig = plt.figure()\n",
    "res = stats.probplot(np.log1p(df['SalePrice']), plot=plt)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过纠偏处理以后SalePrice基本服从正太分布。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 特征变量之间的相关性研究\n",
    "接下来我们要研究的是除SalePrice以外的所有特征变量之间的相关性,我们要画一个所有特征变量(数字型的)之间的相关系数矩阵的热力图:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.set_option('precision',2)\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(df.drop(['SalePrice'],axis=1).corr(), square=True)\n",
    "plt.suptitle(\"Pearson Correlation Heatmap\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "皮尔森相关系数用来表示两个变量之间存在关联关系的强弱程度(即一个变量发生变化则另外一个变量也随之发生变化),相关系数的取值范围是[-1,1],其中-1表示完全负相关,1表示完全正相关,0表示不相关,在上面的相关系数矩阵中的热图中,色块的颜色越浅(如主对角线呈现白色)表示越呈现正相关越强,颜色越深表示越呈现负相关越强。如上图中YearBuilt和OverallCond这两个变量对应的色块是黑色的,说明有非常强的负相关，YearBuilt表示房屋的建造年份，OverallCond表示总体评级,也是就是房龄越长,总体评级越低。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 目标变量和特征变量之间的相关性研究\n",
    "我们完成了特征变量之间的相关性研究以后,接下来我们要进行目标变量SalePrice与我们的特征变量之间的相关性研究"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_with_sale_price = df.corr()[\"SalePrice\"].sort_values(ascending=False)\n",
    "plt.figure(figsize=(14,6))\n",
    "corr_with_sale_price.drop(\"SalePrice\").plot.bar()\n",
    "plt.show();\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " 我们看到大部分变量与目标变量呈现正相关,有少部分变量呈现负相关。其中OverallQual与目标变量的相关性最大接近80%,我查询了一下OverallQual表示\"整体材料和成品质量\",这符合常理,房屋的材料和质量越好,房屋的价格应该越高。KitchenAbvGr与目标变量呈现最强的负相关,经过查询KitchenAbvGr表示地面厨房数量,也就是说地面厨房数量越多，房屋价格越低，这是否意味着地面厨房数量越多,房屋的有效使用面积就越小,所以房价就越低?咱没有住过美国的那种独栋别墅,所以只能瞎猜了。下面我们查看一下与目标变量相关性最强的特征变量OverallQual的箱体图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 9.5, 0, 800000)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "var = 'OverallQual'\n",
    "data = pd.concat([df['SalePrice'], df[var]], axis=1)\n",
    "f, ax = plt.subplots(figsize=(8, 6))\n",
    "fig = sns.boxplot(x=var, y=\"SalePrice\", data=data)\n",
    "fig.axis(ymin=0, ymax=800000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到随着OverallQual:\"整体材料和成品质量\"的数值的提高,价格的中位数明显上升，显示出很强的正相关性。\n",
    "\n",
    "接下来我们查看几个变量的散点图:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EOwIhkxufrEj5DN34ZAWBUM9c39pqWLu11slVIv5zz6w1KQiC0MOImNrSexntock93Rk7T3FjMMplS9/mzEV/4rKlb7N9bx2mqW2PD4SjtsmGiaIwg4pyKSmwrjDX28o8C4IdvW19a2vyYpVS6lKt9csASqnJwH7nLksQBKFn0F5N4myS0tyGsozLdUkSW4dimhqlrP/Xu/c3WMY728VM79pXT0MwknWyoZQ7F44Wetv61laP9Tzgx0qpz5VSe4A7gbnOXZYgCEL3J2EkW3ky7cimypjPbbB0+tgU7+XS6WPxudtcPFdohcRY/uzlv7NoyqiU//WKGWU8tH5nyvGJeGcrz/KiKaN4aP3OZAhJtrJ5bfFsC0JPx+NWluubx90z53tbVUF2AeVKqXxAaa3rnL0sQRCE7k91Q4glb2xPqRi25I3t3HPZKFvlhmyS0kzgd+9/kaYKcsNZJ3Tkn3NU0/yBp6ouxIJJpRTneRlY6CfHY1BVH0w5PhHvnPAsPzennMqaALWBMA+8vp2te2oBaAxG+bSpgWt+sylthyLRr3ikhe5CV1QFDUW05fo284xhjvbrFBkNa6XUDK31k0qpH7RoB0Br/R8OXpsgCEK3xjRNfnD+CNyGC0NBcb6PH5w/AtO0T7qxCzXIJC3lNhTfKv1aStb8kstH4xYjrMOweuCJmhqtNX18njQljxUzyyjye4CYZ9nrdvHD599PvseYIYXcMnF4sshFSb6PyppAcofi5ZvOZO+hoOhUC92GrtJOdxuKfy0bnFwDlYr93lPXt9Y81okKi1K+XBAEoQVulyIU0Xz3qcPeyKXTx+J22d8QXAoWTRnFnesOl+9dNGUUGU4hHDHxuA0WTj6FXK+LxlAUj9vosQUUuiOJWOmSfB+3XTAyZXwevWYcJ/bL4+nvns6+uiDVDSEe/OMObv32yKTRUZznZcWMMuY+WUFJvi+tRPOiKaOSnuzKmgCBUFR0qoVuRVdpp3vdilAUbnzi8Dq6bEYZ3t4YCqK1XqGUcgGHtNZLOumaBEEQegRNYWsZvOfmlNueYxgGT7yzOyV85Il3dnPPZaNsz4lquOnprWle7rVzJ3TcH3OUk4iV/sfBpqRRDYeNi7VzJ3D1r/+SMgbbvqpLMTpKCnwsnHwKQ4tzmRkP/Ui8x53rPmDBpFLmrqlgcJGfqLZWQhCdaqGr6CrtdDu5vefmlB927/YgWo2x1lpHlVKXAmJYC4IgNCNiakryfSlG8vINu5Lb/1YU5ri5eeKI5I0k4Z0pzLFfjrWNEaZ1z5Sj6o4kYqXzfC7r8spR67LLoUg0uYW+5I3tXHvGMKobQpbHFvo9SQ94jsfF+aX9mVI2JDl31lXsEZ1qocvIpipsR5DNOtqdaavc3jtKqUeA54CGRKPWektrJ8Y93puBL7TWk+JVHJ8F+gJbgJla65BSygesBsqAauCKRGVHpdSPgBuIFaa5RWv9erz9QuBBwAX8Wmt9b7zdso82/q2CIAhtwu9xpW353z91FH6P/Y2oqiHEw+t3pNxEHl6/g59degoDC/2W53jdYoR1BoahyPFYGxfhqE62jxlSyLxzTqA4z4tSitpAauLjA5ePtnyPwUV+Xpx/JsV5XkxTc8vEEcxr9oC1fMbhuG1B6GyyqQrbEeS4Dct1NKeHqh619arPAE4GfgEsjn890MZzvw982Oz3RcASrfVwoIaYwUz8e43W+kRi3vFFAEqpUuDKeP8XAkuVUq64wf4r4DtAKXBV/NhMfQiCIHQYGpI3A4h5JW9/4YOMhcbDUZOqutTn/Kq6EJGofbx0kd/DLRNHsPCVbVyxciMLX9nGLRNHiBHWgZimZl9dE42hKKuvH8/5pf2BmEG8eNpoVr61ixUzyji/tD+3XTCSha9sY+ryd7l8xbt8VdtESf7hGNS6pjD3T02V7Hv0mnEce4w/KZtXEwgnjWqIzZ15T1ZQEwh3/h8vCGRXFbYjyGYd7c60VW7v3GzeXCk1GLgYuAf4gYqlfJ4HXB0/5AngZ8AyYHL8Z4AXgEfix08GntVaB4HdSqmPgfHx4z7WWn8S7+tZYLJS6sMMfQiCIHQYTeGo5RZmMGwfk+j3uPjxRSdx69r3UxQ+cjJ4ue2MMEl0s8dKNgzS5e0AagMhDjSE2HMgkEwOvePCk7j9gpFU1jRhas07n1Rz10Un8bNLT+HyFe+mjMXcJytYOPkUZj3+HvPOOYGbnt6aMi8aQ1EG9EnVoe6qeFZByIRpasJRk4ipUVET09SdILdnWq6joR6anN2a3N7pwErgBOBvwPVa6w8zndOC/wTu4LCqSDFQq7WOxH+vBAbFfx4E7AHQWkeUUgfjxw8CNjZ7z+bn7GnRfnorfQiCIHQYdqEgmYxkIGlUQ8yYunXt+/z2xjNsjw9FrA14McKssZINW339eIIRM22b2+c2qK4PETFNFrz095RxHNovD48rSB9/TG6v0O/lq1DA0iAe1i+PwUV+Cv2epKze3DUVyWPevvPclESsropnFQQ7IhGTj/bWpYUnnTSgALeDYRk+m1CQnloAq7Wr/hVwGzFj9T+IGcptQik1Cdinta5o3mxxqG7ltY5qt7rGOUqpzUqpzVVVVVaHCEK3QOZq59DeCnmRqGm5hZkprKPJxlPZlMFIzvHGbjzNQ0HuuHAkOd7udePpLvPUSjbss+pGSymxz6ob6ZfvtRzHplCUu377N9AwvCQfiGlbJ0I8Egwu8pPrdbF27gS+dkwOq647jTFDClNeb2kwW1VsfPSacRT5PVlVaRTaR3eZq92JffVBy52xfS2KI3U0EVNbr6M9dO63FgpiaK3fiP/8fDyJsK2cCVyqlLoIyAH6EDPMC5VS7rhHeTDwZfz4SmAIUKmUcgPHAAeatSdofo5V+/4MfaSgtV5JzCPPuHHjeuYICkcFMledxzQ1n1Y38Fl1YzIc4LjiXIYW59luhYZNa7WOTDcEl1LM/eehTB339ZQqY64MBWJCYesbz/PdTG6vu8xTqzCLXG+q2kciAXFYvzyUwnIclVKU5PuYGw+7Afg/v9uWpkO+YmYZ9cFISnXF+6eO4r7XtlNVH7RMAGsez5oITSnye9hZVS9FYzqB7jJXuxN2yjeZHAUdQdRmHY32UsO6UCn1r3a/a61/a3ei1vpHwI8AlFLnALdpracrpZ4HphJT7bgWeCl+ysvx39+Nv/6m1lorpV4GnlZK/QcwEBgObCLmmR4eVwD5gliC49Xxc/5k00e3Zuhdv2vX8Z/ee7FDVyIIRx+1gRB7DzWlhQMU5nrom2cdx+w2rKsoujIYQXk+g0mnDk6porhsRhl5Pnvvc8jmhhd2+IbXU7EKs2gMRVNUPZoXgVl13WmW47h7fwO3XTCSB17fngy7+cO2fcmS54mwnH55XqYsfzftwWfNDePxuV18rU+OpWFsGColRr6qLihFY4Quw+MyLD8HbpezO2Nul/U6mqnQVnemtf/WW8Alzb6a/z4pyz7vJJbI+DGxEJPH4u2PAcXx9h8AdwForf8XWAtsA14Dvqe1jsa90TcBrxNTHVkbPzZTH4IgCJYEQlFLr3AgZB+i4TIUi6akqj8smjIqo2HdELQuhtAQtDeSEze85nTGDa+nYhVmcVxxbrLth+ePSCkC89D6nWkqHoumjOKh9Tu5c90H3DJxOF63K2mwb91Ty9w1FcmwnKDNg8++Q0G0bnvylyQ0Cl1Jrtdg6fSxKZ+DpdPHkutwyJmhVNrn7/6pozAy7OJ1Z1qrvDirIzrRWm8ANsR//oTDqh7Nj2kCptmcfw8xZZGW7a8Cr1q0W/YhCIJgh10lvGiG3cioqS2rKN59ycm250SyCB/pn+9j+YyytKSi/vnixbTCKswiEYrx2xvPoCEUSRmDrXtque+17Tw7p5wvagLUBsLJ8uMAQ/vlJc9vqfO7+vrxuA2DF+ZNoLohxPINu9i6p5bBRX4aQ1HbZEQr1RJJaBS6koZglLc+2sfTs8vRWqOU4qUtlfxr2WAKc53rNxgxue+17Snr6H2vbec/rzzVuU4dpE1ye0qpAcAvgYFa6+/E9aInaK3FEywIQq/ArjBIjsfeW+NxKW46b3iyrHnCw+PJsIVpFz7izuDVdLsNThpQwNq5E4hETdwug/75Pkcz9Xs6LcMsEoSjJp/ub0wbg6r6IAr44fPvpxu2LpX0OicMdtM0UUpRVRdMia1eNGUUT7yzm1lnDmNAnxzL4hpWqiWPXjOO4SX5XVKgQxAA/F4X44b15epHN6YWvPI6+2DnMRRV9cEUFZ3BRX48PTSvoK2r8uPEQi4Gxn/fAfybExckCILQFfTL81mqNPSzia8GCEc1v3v/C1Zddxpv/vBsVl13Gr97/wvCGdzcHpey3G7NZIxDzLgeWOjn68V5DCz0i1GdJVGteWj9zrQQnmXTx+J1G2lb0ksuH43bUCkqHRpNIGxyqCnCg+t3pIT13LnuA+6+5GRGfq3ANvHVSrVk9urN1ATCXVKgQxCg69Q53C7FshZr4rLpY3tsjHVbS5r301qvTaiCxHWmJehLEIReg2Eohpfks3buBMJRE0/cK5zJqDEM+M6ogVTWHC4s8p1RAzEy2LwRk6Qx3lwV5Nozj3fgrxJakuNxUVUf5IHXt6cUcCnO9xKORulX4GPh5FPI9brQwDG5nmRi4vml/bl54ggeXr+DKWVDKM7z8uOLSvnmwGNY/MedwGE1g0x5pZliqe087YLgNGGbQi1hhwu1RExNxafVPD27HFNrDKV4c9tXnH/KsY726xRtNawblFLFxPWglVLlwEHHrkoQBKGTMU3N5zWNKXJ7TcXRjHJ7BopAKJqmJGJYyunHcBuKb5V+LUUVJOEVbe36Wsbkiiez/fTL8/HozHHMXrOZuWsqGFzk5/FZp7HvUJBgxMRlKE46toAvagKUFPj4pKqBxdNGUxsI0yfHzcPrd3DtGcNS5PaWzyjjn0b0IxTRNIaifFEb8/TZSeVJLLXQHcnxGtw75RRchgtDQXG+j3unnOK4Xr7XZVA2tDglBGXZ9LF4e2hydlsN6x8Qk8M7QSn1NlBCTM5OEAShV1ATCFrK7R2T66Y4L8fynLDN1umzc8pt+4maJgV+N4/PGo+hwNQQMaNETXuvkF1MroQJZIfPYyS90oZSNIVNbnpma4qhvPa9PcyccFzKfFg2fSzXTBiaoiiSKKLx+KzxVMcLaeT73JTk+2yl8hKqJRJLLXQrNAQjmvlPHc4ZWDp9rE2JvY4jFDW5MZ6nAnGlpKe2sHau/TranWnT44DWegtwNnAGMBc4WWv9gZMXJgiC0JkEQtZVFAMhe4PXrrBBpmp5hlLUBSJct2oT5y1+i+tWbaIuEMkoLWUXk1vdEGrPn3jUY5qafxxq4kBDiFDU5N7ff8SBxpBltbk5Z5+QvNmPGVLIgkmlBCMmg4tyLce8tjHEFSs3suClv9MUjnLHhSOprAkQCEfT5kNz1RKJpRa6C01hM5mIDbF5Pf+pLTSFHQ4FidooJWWSZOrGZPRYtygO05wRSqmMBWIEQRB6EmYWRrIni8IGEVNz69r3U25et659n+cyeLlF3/jIsfL6L5s+llyf2/J/63GpdhWTSTzkJMbzqe+ezuAiP7v21dMQjKQZzoahKM7zJsN7qhtCEt4jdCmmjeSoqZ01cF1ZFNrqzrTmsb4kw1e2BWIEQRC6HYnFvTmtLe5el3VBhUyxgRFTU5LvY8XMMp6bU86KmWWU5Psylu9VyvraVA8toNAVWHn9b3xqC1qT/N+OGVLIipllvDBvAi5DcX5pf+adc0Kbisks37Ar2VdlTQANySIzVrsLCUP/sqVvc+aiP3HZ0rfZvrcu44OcIDiJYbPOOF2oxVCweNrolM/U4mmj6aF2decUiBEEQejuGEbMEGqelLZoyqiMCh9NEZNH3tyZkkX/yJs7+WmGAjE+t8EdF45Mhp0kYrm9GeTzXAoeuXoMNQ3hZGJlUZ6HHqpG1SXYef0DoQj3Tx3Fqrd3M//cE6lpCBM1NTv31nP7hScRiqRWVUwUk1lzw3iUUngMxc//63+TxWQg/kCmVEqRmZa7C3bhPVK+XOgqlLJeA51+fncpRWFuat5J1Izi6qGOg7YmL6KUuhg4GUhm8Witf+FGqMcnAAAgAElEQVTERQmCIHQ2pkm7qyhGTU2h38vx/fJwGYq+eV4K/d6MXkfTJuFxbYZQEI/bIBwxUxLpllw+Go9oWbeZhNe/5XbzlwebWL5hF0tnjOXT/Q1pyatD++VZFpPxuAz2HmrCNGHWmcPY9lVdytiYWnPXd06iNhBmXcWeNMUPCe8Ruhtaw5+3702TAh1aPMzZfoEDDWFuf6Ei5bNX6O+Zybxtrby4HMgFzgV+TUwRZJOD1yUIgtCpZFNFMd/rYsaE41Kk85ZOH0tehkpl4SxKmtvFZf92/hnt/CuPXlw23rgHXt9OVX2QSNT6gefp757O0ulj0+bFwUCY7z/7V0ryfdx9aWmK9nVhnpfpv/7L4VjuGWUU+T0p1yOSe0J3o9BvMOnUwSnr2bIZZRT6nX2Az0ZdqTvTVo/1GVrrUUqpD7TWP1dKLQYkcVEQhF5D8yqKzb0115xh762xCwXJ5OW2K2meKZY73CIcAWI3H6cLN/QmDMPgz9v38sT143EZikhUs/KtXVTVB1k2fSxRm8QtTcyTt+q602gKR/nyYBOPvLmTOy48icqaAJU1AX7+8jbmnXMCubgYVOjnqrgeb+I9bnyyIi3EI5PknmiWC11BbcDkxhYKOTc+WcFzc8qxURztELJRV+rOtNWwTvzFjUqpgcABwNm9AUEQhE7EUHDWyAEp3prWYqyVIhmXC7FkxvnnnpgxJrFfrpdlM8qSN7CEV6hfrv22p3g3j5w+XhdXlw+lqi5IdUOIdRV7+P7EEcw/7wSWvrmLW7413PJ/DDD5V28nVUT6F3iZdeYwfG4X55f2Z0rZkORD1WP/80nS4G5OIpY7EvEkS9E3l9xrbkADolkudAmRLHbTOgKvy0j7LK2r2IOnlxeIeUUpVQjcB1TE237tzCUJgiB0PqYmrfDHnes+yCiD51IKrUmJy334qjEZk248HheFLQrE+NwKj8feSJaCItlhmpr9DUGipsmB+jBzmz3MLJ42msZQlPwcN/POOQG3AQ9eeSrff/avyWMevPJUvqxNVRFZOPkUcjwG735cxU8uLk0x1G86bzi1jWFLA31XVQOHmiKcNKAgxbhumahYVReUpEahS7DbTWutKuyR4nUrbj5vBDc+1czZML0Mr7tnPki2pmN9GrBHa70w/ns+8DfgI2CJ85cnCILQfiIRk331QcJRE4/LoH++L2nM2BHVMRm85mEdyzfsyqjhamq4OV6xD2JG0M3PbOX5uRNsz6luCHHVo39Ju3llMpzsvJviwbSnuW71gkmlLHxlW8o4/fD593lg2mjOvn8Dg4v8PHTlGIrzvSycfAqFuR4KcjzkeBQHAxGevGE8HpdBbSBMv3wvD7+5k1smjkiJo140ZRSPvLmT2f98QlpMdvNY7rVzJzCw0G973ZLUKHQVHpdi7dzTiZqKqNa4lMJlaMcN61BEJ41qSDzEVmRcR7szrfnZVwAhAKXUWcC98baDwEpnL00QBKH9RCImH+2t4/IV73L2/Ru4fMW7fLS3jkgr8cg5LoOfXVqa1KD2xn/3ZdiODEdtYp+j9n1lazglvJuDinIpKfCJUd0KzeXsCv0ey/95SYGPMUMKqawJcMuzW/nHwSAPrd9JYyjKfa99yKf7G8nxuAhHNff+/iMWvrINTUwFpGW1xjvXfcCUsiH07+PjyXc/45nZ5Tw3p5wFk0qTsnuxanKZ52Ei7Kc5EvYjdAZet6IhZPLxvnr2Hmzi4331NIRMxz3HoSzW0e5Ma6EgLq31gfjPVwArtdbrgHVKqb86e2mCIAjtp6o+aFmi+vm5Ezg2g6fQNjA6Q1hHNhXDlFKW8YRS7KVjaf4AUxuwDs/4vLqReeecwNw1sfnSL9/LvHNO4Il3dnPtGcPSFERe2voF1fUhji/JY8GkUpZv2JXUqa6sCVCc58VtKG751nAU8MPn30/r091K3KiE/QhAlySwBsOa/XXBNMnJPr42KzNnhd062hnOAyf+z615rF1KqcR/dCLwZrPXnP1PC4IgZEG23g9TaxpDURa89HeuWLmRBS/9ncZQNGMoSKKgQssqfJnW5RyP4uaJI1j4yjauWLmRha9s4+aJI8jxiGHdkTT3/C7fsItlLSpkJqoiFsZl8BIPRIV+D1PKhqTF2z/xzm6mlx/Hgpf+ztn3b2DhK9u47YKRjBlSmDy/b56XuqYwV67ciMelLKty5noz33abh/28fee5vDj/TElcPMroqqqcdrJ3YYf79RgqrZrp/VNH4XF4zjv1f27NOH4GeEsptZ+YMsh/AyilTiQWDiIIgtBmOsMLk633I5KFlqpCWRZUOL7f8bbnBEL2klbktecvFaxIzDHTNFkxo4y5T1awdU8tTWEzqTVdGwgnY55NrVl13Wl8vTgXj8vAUIriPG/aw9mUsiF87+ktaeEfifjtX109luc2fcbYocWU5PtoCEVRSvH07HIUmqawyaN//oTvf2s4hbmZ/warpEbh6GF/g3UC62/nn0H/Aud077pK9s7jVvQr8CU/n42hKP0KfHgcDkFxqvppayXN71FKrQeOBf6gddJ1YwA3Z92rIAhHHc2TyZyUEctxG5YFPXJaS17M4qaS41GWBRUyeZ/tJK2iPVSztTuRmGNL3tjOlLIhfHNQH56dU04wbOJzKw40Ginz4jfXjSMY0SkV35bPKKMo15P2cGZlbFfWBDjpawWsuX48++tD/GvZEAwF9075Jp/ubyTX62J/XZCiPA8/f3kbVfVBbnef1Nn/FqGH0RS2zsNoCjsbc+x1G5ZOCacrvIYjmmP8bnIH5BMxY8mSHrciHHF2TXQqUbjV/5bWeqPW+kWtdUOzth1a6y1H1LMgCEcVdt6B6oZQh/YTih4u2pJIHnvkzZ2EWksacxmWSWOZtFQbbbzPjSH7vjw2/bQWeyu0zv6GIEve2M61Zwxj4Svb+Ky6kdrGMNeu2sQ/3beBR97cyerrx/Pi/DN4dk45uV532vjNe7KCL2ubWDajLGVruqTAZzlun1Q1cO7it7h17V85FAhTH4xwoCGUElIUCEX58UXfYMWMMlwGPbbwhdA5uJWyXiMcjgYygCWXj06Z90suH926oXiEeN2KvYdCXLFyI2ffv4ErVm5k76GQ40mTTiUKS5y0IAidQmfJiIWjmqq6VGO9qi5EJJrZmDFU7KaSKB2evKlkWNujprVEXybvc/98H4/POo09BwLJbc8hff30z5et/yPBNDWNwWhKfHTU1CmJrH/Yto9tX9Xx+KzxRE3NPw42Wc7JHI9BNGry1HdPx1AKU2te3voF908dlQwXSsSB3vfa9uR5t659n2dml6dVXrz9hQ94ZnY5tzyzlar6oBR8ETLi81jvuvk8zpq4TRGT5zdXpoS2PfrnT7jpvBMd7dfOQfHcnHKKHAyPcypRWAxrQRA6hc6qHpjjNrjjwpFpBpCvle1Mu5vK9zLcVHI8Lsu+cjIUezGM2BZn88z7R2eOEyPrCNnfEGT3/gYGF/mTDzrF+dbhGw3BCC5DMaCPL21Onl/aHw3cFNcnT4zpWSNLKMrz8sC00Sigfx8fP3ju/aQqSOK9TZvS6MFINHns7NWbeW5OueiRC5Y0hQ/vuiUe2B95cyd3X3Kyo/363AaXjR2UEtp2/9RReB0OBemq8Din6gPI3qMgCJ1CwjvQfJuxLd6BSMTky9oAn1U38GVtoFU96qjGMgmxFYc1/mY3lfMWv8Wsx9/jsrGD8Ge4qUSipmVfmbSKqxtCzF7TIiRmTceHxBxNJLzVv//bV/jcRlKL3C7spiDHzUPrd9AQjKaFfPzk4tKkpxAOj+mBhjAKxZUrN3LFyo3s2FtPVX0w7b2jprbs8x8Hm5K/V9YEqKwJdJrag9CziGrNH7btY+6aCq5YuZG5ayr4w7Z9RDMoFHUE2mbtdLjbZMXH5rQmW9pROFEfQDzWgiB0Ctl4ByIRk08PNKSETTT2jTC0b55tJcVw1LQMz2hNbi9ic1NZm6H6V9jG05JJnkoq63U81Q0hdu9vYNq4IVQ10+F9fu4EyyqI9/7+Q6aUDSHX6+LZTZ+l7FI0BCOW45PrdRExTcYMKWTrnlqWb9jFoimjUrSu7586iuUbdlmGFP3y1Y+S7ze4yE9tINxhKgRC78LjMiy17jPle3QEXVWoxYjLlrbUje+pGzliWAuC0Gm0V0bsQGOIhmAkpa0hGOFAY4j+faxlp+xCQVpTBcmmiqLbRtovUwngzgqJOZoIRaI8tH4nD101JiW+2dQar0ulPGQlqiDOOesEXC7FWSMHpGx9r75+vOX4NIaifLr/cEGZrXtqeeKd3Tw7p5zq+hB1TWEAppQNBhRr505Aa43HbVDfFEl6t5uXOAd5qBLS8RiKm88bzo3NHgiXTR/ruK6z3XrmtOc4quGJd3anfE6feGc3P3U49MUpxLAWBKHb0rxoS3MjOVPRFlPDqrdTF+lVb+/m55eekrEvj81NJdPNzGsj7ZcpJlEq63U8XreLkgJvMr55zJBC5p1zAscW5qA1LHxlW9q49s3zEo7qtEIw9/7+w7Tk0kFFOZha86N1f+cnF38j+R63TBxBSa6X2sYwd/32bymSff3zfcldlX55mhfnn0kgHGXXvvqkcZ94H3moEprTFDGTRjXEk/me2pJRU78jcBuKX109hgMN4eTc75vnyego6Kh+Z505LM0Z4nS/TuGYYa2UGgKsBr4GmMTKoT+olOoLPAcMBT4FLtda16hYPd8HgYuARuC6hKSfUupa4N/jb/1/tNZPxNvLgMcBP/Aq8H2ttbbrw6m/VRAEZ8imaItGW5ajhsyBgm6XYan6kEkGzzQ1Prfi8VnjMVTMqI+a0Ywxs04lzBzNFOa4+cnFpeS4DZ6fO4Ecj8GNT21hwaRS1lXsSdtmXjp9LMs37GJ6+XFpuxRVdSGawmbKw9ySy0fjdimq6oMc4/fw3JxyBhX5Kchx4fO5OWlAAWvnTiASNXG7jBSjGg7v1JjxUJPm3mt5qBJaYpcAm8mh0FH9tpz7i6eNxmxl7TxSDCDX60opEJPrdXVKEqATRcuc9FhHgB9qrbcopQqACqXUG8B1wHqt9b1KqbuAu4A7ge8Aw+NfpwPLgNPjRvLdwDhid8YKpdTLcUN5GTAH2EjMsL4Q+H38Pa36EAShBxE1NWccX8zss45PUerIZLhqTZoX8s51H8QqG2YgEI7y4pYv2qUK4nYpDMNgz4HG5A1hcF8/blfmhVkq63UcpqnZUVXPy1srufTUwdQHI9y6NmYYFPo9/GHbPqrqQiyYVMrw/vl8WRtAa82N55yAMhSrrjuNh9bvTHqQb5k4PEWiLyGjt+aG8SyeNpo7XviAqvoga+eUk+fxUFUXJBSJ4ve6iLgU4YhJTSBseYM2DMWJ/fJ4bk55shBG//zDCVOdUZlUaD+RiMm++iDhqInH4sGpo8mxCRfLcXhnw9Tww+ffT5n7P3z+/VbXziMlojWGavFZUcrxZE3T1Hxa3cBn1YfX7+OKcxlanHdEnzvHDGut9VfAV/Gf65RSHwKDgMnAOfHDngA2EDN6JwOr49UdNyqlCpVSx8aPfUNrfQAgbpxfqJTaAPTRWr8bb18N/Asxw9quD0EQehD5PhezzxqWTB5rDEWZfdYw8nz2Nxi7CoqtSTfl2EhNZYrNjkY1bgNO7J+PGb85RMwo0dYkSIQOo7ohxIN/3MGPLvoG//fVD/nRd77B4mmjqQ2EMXVMoSORbHjf1FEU5XmJRDUzf7MpxYOtgP31IYb2y7WcPyquZ11VH2TZ9LHk5RjsrKpn9urNlOT70uL6rbSqIxGT7fvqk4Z7ImzkpPhxnVGZVGgfkYjJR3vrLMfMKePa61Ysm1GW1HZOVHR1umBK1MZT3hlqJA+/uTOWUIyLUNTk4U6QF6wNhNh7qCkt1LAw10PfvOwdH50it6eUGgqMAf4CDIgb3Qnju3/8sEHAnmanVcbbMrVXWrSToQ9BEHoQkaimtjGcUsWutjGcsdiLYSPd1JpxorGRmsp0faZm5mPv8c/3/Ymz79/AP9/3J2Y+9h4RkU/rNKKmyY8u+gZuQ3HtGcOY+ZtNXLFyIwtf2YahFI9cPYbzS/tz2wUjkw9N33s6NX51/lNbyPG4eGbTZ6CxnD+VBxoZWBjTyH74zZ00BHXSqF5yxWhKCnJYc/14npl9OiX5Psuqovvqg2ne8HlPVrCvPthplUmF9pFpzJyiMRilYvd+np5dzlu3n8PTs8up2L2fxqCzSa4um4qPLuWsQe8xFHPPPoGFr2xLfnbnnn2C48magVDUcs0PhBwuaX6kKKXygXXAv2mtD2U61KJNZ9Henmubo5TarJTaXFVV1Z5TBaFTOVrnasTUSdkyOLwtn8lwzfUaadrEy2aUkevNvNwFIzGZvhUzy3huTjkrZpZRku8jlEE3OxKvvNjyHCcMa9PUVNUF+aKmkaq6YLfUPu7seRqJmNQHI3y6vxG3yyAUMVk8bXRyHB77n0/ok+PhJxeXEoqPb6HfY+mVOxgIc+0Zw3h202esaDF/Fk8bzep3PyUUMZOawglZx59c/A1mPLaJb/3HW8z8zSYA7r60ND53Um/QdsozkajZJTKMPWFOOUVb52qmMXMKt0tRNrSYqx+Nlfi++tGNlA0txu2wx9rjUiybPjZ17Zw+Fk8roW1HijIUBTluFk4+hefmlLNw8ikU5LhRjquR2Hnoj+x9HVUFUUp5iBnVT2mtfxtv3quUOlZr/VU81GNfvL0SGNLs9MHAl/H2c1q0b4i3D7Y4PlMfKWitVwIrAcaNG3f0rChCj6O3zNX2xpBmU5ErEDJ55a+pFRRf2Pw515wxDDKUx/W5DX580Ulp+sOZFD58WVZ5bC+mqXtEmEBnzFPT1NQGQgRCUVyGoqouyDObPuPm84anbOk+dOUYBvTx8dXBJqobQqyr2MO9U75Jns/NC/MmUN0QYvmGXWzdU8vgIj/VDSEWvrKNBZNKOSY3dpP/et9cPq6q57H/+YSbJ44gGtexrqoP4nEZ3DJxOP/23F/TPF4LJ5/CLROHp6l9JArWpMkzugzb15xSDOkpc8op2jpXM42ZU0Simlfe/yJtDbv2jGGO9QmxkAy/10hJxgbT8QIxwYjJA69vTwkFeeD17Y7L7eV4bGLZj7B0vGMzI67y8Rjwodb6P5q99DJwbfzna4GXmrVfo2KUAwfjYRyvA+crpYqUUkXA+cDr8dfqlFLl8b6uafFeVn0IgtBFJG7kly19mzMX/alNVedcWYR1KEVSmzhRQfGskQNobTdTayy945luKhFTJ6X9nptTzoJJpax6e3eHe6wlTCBGItlo+z/q+Pl//S/haEw1ZkrZkDR5slue3cqOvfVMXf4uC1/Zxg/PH0koqrly5cZk220XjOT80v4smhIr7FJZE6A4z0vUhIfW78RlKIrzvNx+wUk8vH4HXx0McseFI1l9/Xj65/sY1i/PtpjM0H55aWof/fN9LG/hDU9I82VbmTRbZE61jZI8r+UOWImDSi5ul2LS6NQqsJNGD2o1KbojqKoLcd2qTZy3+C2uW7WJqjrn54Oh4IZ/Oj4lFOSGfzoep//cfnk+y89cvyOIrwZnPdZnAjOBvyml/hpv+zFwL7BWKXUD8DkwLf7aq8Sk9j4mJrc3C0BrfUAptRB4L37cLxKJjMCNHJbb+338iwx9CILQRVQ3hFjyxvYUfeklb2znnstG2SpkuA1lWcUuk75ptqog2VQdMxTMP/dEahpixUG8LoP5557Y4RXDpFpjjOqGEJ9VN/LMps+Yc9YJBCNmUv3DzsBN/Pxl7eEkpUTbnes+YNV1p3HHCx8kPdfF+V5qG0P8+KJvUNsYiu1KvPABAEOLc6luCJHndXEgEMLjstY+bwxFyXEbaQ+AbreRUZqvM2UYZU61jdqmCA+v35Gybj28fkds3fI4s5sQjmoefnNnap+dkMwXzkLetGNQlmokmaredgSGoRhekp/2eey2cnta6//BOg4aYKLF8Rr4ns17/Qb4jUX7ZiCt6oPWutqqD0EQug7TNC2NUNO0N1w9LsXAohyemV1OVGtcSmEYOmPMX7aqIAnveEsjKdMiayhFwKKATUvpqCPF63ZZljg+2gqLhCIxfdspZUP4t+f+yr3/+k3OL+1P3zyv5djVBsLJ33O9LtvY6oRRvXxGGYcCYX71p49ZMOlkAuEIOR4Xw/vnc9nYQcz8zaYUBZCSfF/ag9/9U2MPiiX5Ng+LboOBhX7L1zpThtHJCqC9STYwFImmeW2r6kKOPoAohaUWv9P/wmzXziOlK+LYITZPE8o+HRkOJZUXBUHoFJSNEaoyGaEaGoJRvqhpSqmCl+Oyv/kbWRjIEMtMtyoQkykzvbM8PEV+D7dMHJEm+VXk93RoP92VhKEW1ZqBhX5yPDEjeetnNdwycQQvbP6cX109Nqn2kRi7+17bnnyPxlDUcl587ZgcNtx+DrurGljw//5OVX0wWVDo+sc3s3DyKdx47gl8ur+RxdNG0zfPm1QXqawJ8MtXP+KBaaM59pgcDKXwuBTFuV5HdY47AqcqgPa22G2/12WZR+H3OvdQq21KfDvtsc6m+mxHkI1ToyOwC4d6cf6ZR/SA270/+YIg9BrCUdPSCM0UahExdZr0USAUzRjD7DUUD155akrc3INXnoq3lUXa61b0K/ClZKb3K/Bl1I6N2qiCdLS6Qk0gbCn5VdPMI9tbScRV//2Lg1TXhwhGTAb08fHwlaO4rGwwD63fwVkjB/CrP+3k/qmj+NNtZ/PUd09nSN9cSgpiRuLgIj9FeR4WTxudpvbxi//6X3ZXNTDr8ffYuqc2GSISiupm4SQqKfl4MBBOMQC27qnlypUbCUdNbnlmK1OXv0ttU6Qr/lXtonkF0LfvPJcX55/ZIcZvb4vdtqv+6qSkZiLEzBtPkEyGmDlssXndhmUOQKYE7o7AEw/5a97vkstHO27QOxUOJR5rQRA6BTtpo0xlejWxG1tzL/eDV56aUVfT5VL08XtSyuP28XtwtZIJEwiZvPDe50wd9/XDmfjvxTLxi2zURPwea29WTgfHXh7N8bA1gSDV9cGUObB8RhnlJ/QjGNH8+KJSIqbmmwOPwdQw87HDhV9WzCjj7ktOJhzV/PLVbVTVhVg4+RSG9suluj7EPb/7kK17arnhn45P6bOyJsChQDgZLx01dbLoTFPY2vO950CA2y4YyQOvb+8x4+JE6Elvm6uhiE3uRQYZziPFULEKns3n/JLLR2PYRtd2DEpB33wPz8wuTxa8crloNfH7SMnxKArzvClrdmGelxyPsx07FQ4lhrUgCO0mmxhKt2EtW+XK4IYxteb7z6bKmX3/2b+ydq59qEVT2GTWqvfS+mkteTFialb896es+O9PU9qnlw+1PSeqrb1Zz8/r2KQbJ+NhuztNITNNreW//lrJpNGDufGpw6ExT333dKb/+i8px819soI1148nqjV3X3IyEVPjMhSGim0/33HhSJSKGZdv3HoWTeEoXx5sYl3FHoIRk6e+ezpawz8ONbHo9x9RVR/kkavHsHjaaH74/PuU5Pu4ZeJwvl6cy1e1AZ54Z7elzN7RRG+bqwqY+89DUx+4N3/uaJ92+v2OlxaPaj7b35jmKDi+Xwad0g6gIWi9Zq+dU84xuc7161Q4lBjWgiC0i2xjKA2FZQxzJns8HLX2cmeqvGinfd3a1q1dnJ8rwwWaNn11dCiIUzeAnoDVTsfUcV9PxjlD7H9eVRe0HItDTRGUgutWpZaqf3HLF1w2dhC3PX848XDRlFGsq9jDzRNH0C/fw7TlG1Nee+D17dz09FaWXH4qL8ybQFVdMCnzlzhmaHHuUTEudvS2uZrjMZh06uDkfEvI7R2p1nEmstHv7wi6ShUknOWafaQ0D4fqyERbMazbwdC7ftfVlyAIXU62CR+hiMnm3Qd4utk240tbKhlko5AA2SW1uA1lqaCRSaIPYtudi6aMalcmfmd555y6AXR3QqEIhjo8B8YMKWTeOSfgcRtpN+LqhpDlWOR6XWlG+O0vxGT2Wrbfue4DFkwq5cYnK3hmdnky/GP5hl3J1+auqaBvvpeoqdO0s+9c9wFr507o9eOSid42V5vCJje2yG+48ckKR73HXZXMZ6cK4nRFzq76e8GZcCgxrAVBaBfZxlDmeV1cOmYgoYiJoSCiNZeOGUhehuz6bJQ6/F7DUkHD30pJc2wy8X+WIRO/OM/L6uvH81l1YzI28DiHPJadKcXWHTBNTVVDiIOBMIumjOKJd3YnJchWXXda2o14XcUeVswoY26zcV86faytPrnLUJbtCU3scNTkipUbkw9YL239gpO+VsAff3B2LKlMYXm+drpMXQ+gN83VbHfAjoRs1r0O6bcLqkxC7O/91dVjONAQTq6jffM8jv+94Iw0pBjWgiC0i+YexASDi/ytajdr4GAgwvxmW+dLp48lz2u/DLkMRXF+alJLcb43Y3hGMKwtFTSeb6XYgNtlMOvMYWk3s9ZuKsEWSUaPXjMu4/FC26gNhIiYmkOBMIV+Dz+95GSuXBkLzXj0z5+wdPrYlLl088QR+DwGa64fj6ljc+eZv3zKFeOPs5yvUVPbal8PLvInE2Qra2Kx0zefNzwZw52Yu+eX9ucP2/alnN9TY4kFa7pCgk4pRa7XlbLu5XpdmaVJO4Bcr2L5jLI0p0Su19l+fR4DQ6mUdXTZ9LH4HAy3AeekIcWw7sG0NzTl03svduhKhKOJbGKlIWaAPtKimtgjrVQTMwzweVwM6ZuLocDU4HGrjLJT2VRQBGgKR7nvtdTKkPe9tp0HrzzV9hyndFCPdiIRk7qmCC4jFtqzry5IIHx4p2RtRSUAq647Da/bQMXDiiaNHsihpgj9+/gIRUymnfZ1DjSEeOTqMdz09NaU+fronz9Jm8cJz/jS6WOpbzosZWhVMn3+U1tYff14tn1V1ytiiQVrXDbVX2K3fwEAACAASURBVDM93B8pTeEoT238nNlnHZ9MmHz0z59w03knOtYnxJIIH2pRZfKh9Tu4+5KTKXQwiTAUTQ+ruvGpLfx2/hnOdYpz67cY1oIgtItg1OTFLV+w6rrTUhf9icMznmdXTSyTE6YxZHLPK9vS4qV/esnJ9LVJVM82Xs8wFFX1QeauqWjzeb1NWqw7YJqa7fvqmLumgnv/9Zvc9du/sXja6LQY6rUVlbzzSXXSCHiuopIRx/Zh+YZd/GLyySlJhUsuH80L8ybQFI6FIWngqtO/zrHH5PDsnHIaghHyfW40mtsvOIlH//wJU8oGJ6+pOM9rOc4HA2GevOF0DEPh9/TsWGLBmqjWeNxGivfY4zYyyoQeKV63wWVjB6UkTN4/dZTjetIRU/OHbftSdmEAfnJxqaP9hiMmJfm+FIN++YZdjkoaguhYC4LQTcjzuiwX/bxWYpi1JmlUw+Fkr0xJQFGbhf7fMyz0Xpdh6VH3thLSkU1cY2+TFusO7G+IPdxU1gTwuGJJiokHqpbVFRMe5qvGH5dU7bhl4vA079eta9/ngWmjuXLlxmQ/g4v8rLl+PDN/s4ml08fy2H/vTHrCBxf5+c43j03+bFsyvTFM3zwvA/vkdPtKi0J2aE1ytyNBW+Q7jwTTRp1jrcPqHF1VedHjMizrAXgcju0WHWtBELoFoYiNdnMrMcx2BWKiGTw/dgofmbZhlYJ+LeKy++V7Wy1y4HEblnGNngwGU2+TFusORE0z6bnqm+fl/NL+LN+wi9suGMmrH3zB6uvHc6AhRHVDKK4bPYJAKMovX/2QqvogXy/OtZxnJQW+5E00ceP+x6GmZFjHwsmnsLaiMhk/3S/fy4bbzmH3/gaWb9iV1K5ufr7f6+Ke323jnstGSehPLyWqtaU31UmPtW3CpMOJsW6XYtmMsqQKSkJa0N1Kca0jJWJTldfpBwnRsRYEoVsQMa1jmCNm5m27bJIefW6Dm88bnrKtv2z6WHwZjN1AKMqjf97d7vjEQr+X2pwwBxoOx9YW5Hgo9Nsvsr1NWqyrMU3NgfowC1/ZlnJjf3j9jqQ32uNS9M3z0i/fx79POpmoaVKU6+Gnl5Syry7IV7UBy3lWVRfk8Vnjqa4P0hiK4ve6+PnL24DY/B3SN+aFTMT+Tykbwvpte5kx4Tje+aSanfvqeeq7pxOOmriU4h+Hmvj5y9vYuqeWuy+R0J/eSo6NN9XnoDfVVlPf4eTFiAkVu/fz9OxytNYopXhz21ecf8pAR/sVHWtBEI5qslUFyXEbaUoOS6ePJSeDkRyOah5ukfD48Js7+fmlp9ie43EZvPNJdXJbP3F9t357ROa/y1B8vSiXHI+LSNTE7TLon+9rU2y2eCs7hv0NwaRcHhzWDH5mdjl7DzVR3RBi4SvbuO2CkYQjmrlPVqRUP2wIRnj5r1+m6ZHfP3UUxXke8n0uFD4+P9CYNIrhcEnyWY+/FyuFPrOMB/+4IxmCtOq603C7DFyGYvqv0yvESehP7yVsala9nSrDuert3RmTro8Uj03CpNMhGW4DyoYWc/WjG1McGU5HOXWVzB+IjrUgCN0ApUjbFl88bXSroRbhqLZUBclkJIO2THgEe0+Gx6UsDXhPK9uZpqnZWVXf4dJLQttpClknE+2vD1LdEKJ/gY+7vvMN9tUFuS1eUvy2C0amzY8/b9/L6uvHYyiFUuBS8ND6j7n8tCHc87sPue2CkVTVB4HYDXzFjDKiWvPnO87F73FR5Pdw67dHsu2rumSS5Orrx/OL/9qWZrSvmFkmoT+9GMMm6drJJcHlUhyT60kJSzsm14PL4ZCMsI06h9Ol1H1uxbLpYy12JnvmuiuGtSAI7cKlFPm+1FjkfJ+r1W3KcNS0TkScZB9CYmaR8NhkI+v301Y8TCKd1/XYbYHvq4slNK6YWcbNz2xl8bTRVNYEWDCp1HJ+PDu7HJdLobXmk6oGFv9hB1v31DKxdABV9UEeeP2wrGJjKEooGuWype/y9p3nJse6+RaxUopIfP5W1YVS5lY/Cf3p1WSzBh0pgbDJA69vZ0rZEHJxEYrGfm9tDTtS7CovOl1KvSlsWu5MOrkr4CRiWAuC0C5MDXOf3JJm/LSWvGjYJCJmCiGxS3jMlDiUjZIIiHReV2OaGreNMst9r20HoNDvoSTfR988Ly/Mm0BhrsdyzJoiUe575SOuGn8csx5/L/la8+qMc9dUJHdbfvFfH6aFdLTcIq6qCzK4yM/WPbVJScbBRX5enH+mk/8WoYvpCmMzamqq6kIpbVV1IcdLi7u7KCQjqm3W7EliWAuC0MVkU541EjHZVx8kHDXxxOOKM0mHZVuAJcdtcNN5w9sVY20Xz52pApnX5ubQmnSTSOd1Daap2d8QpDEYxe1SvLjlC56eXc6+Q02UFPioaQwlwzYMpbjjwpFJqUer0uaDi/zsrw/x/XglxuZKIDedNxyvW/HAtNEM6JPDp/sbuPf3H1FVH2xVDUAUYI5OjCx18Y8Ev9s6YTLTWtkR5HisVUFyPM7uyOR4rNfeHIcrLzqFGNaC0EvIpjxrJGLy0d66tBK2Jw0osDWuXXae51ZuNKGImTSq4XD1ukySStloUrsMxcNXjeHmZw5X2nv4qjGtVkoTw6nzsZqz908dRWMwTDBi8klVA89s+owFk0oZeEwOhbleroonVgE8tH6n5fwYWpxLUyTKL3/3IQsmlVKc56U4z8uzmz6j/IQSvnZMDkMK/eT73Dxy9Zg2PYSKAszRiddmF8Xr4LiHbXSsnY51bgqZPNyi8uLD63fws0tOBpuCXB1Bvzyf5drbL69nhuCJYS0IvYRsYoT31QeTRnXinHlPVrB27gQGFvotz8nG8wwZtFkzbG9GtUkff2oSTx+/h6i2944X+T0cagqnnFOQ46bI78l4fWI4dT5Wc/b2Fz7g8Vnj+fP2Sq46fSg/uugb7K8L0RiKEow0pcyhrXtque+17ay5fjz76oLJMvT/eeWpLH1zF1eNP47jS/LYc6CR//v7D/n+xBEcW5hDod+blRqAKMAcffi8ioFFfh6fNR5DxULhPG6Fz+vcutBVsc52IRkLHA7J6G1rb8/0swuCkEY2McJhm7COSIawjrCpLT3P4VYWfXd8S7U5g4v8uDMsnqYJD/5xB6H49YSiJg/+cQeZJLM9HhfHFeUyYkA+XzsmhxED8jmuKBePp/WQjoThNKgol5KC1qX2hCPDbs4W+FxMOnUwMx77C+c+8Bb1wQg/fP79ZFnz5lTVB9mxr54rVm5k7poKquqDREzN2opKZj3+HoZSDOuXxz2XjeIbx/ahb56Mq9B2giHNvoNNXLdqE+ctfovrVm1i38EmgiHnjFyXzVrZ2q7bkfdrdEm/0LvWXjGsBaGX4HW7OL+0PytmlvHcnHJWzCzj/NL+GWOEE/qhzWktWcXOGG8txtqIb6km+ktsqWZaQFVc6mrhK9u4YuVGFv5/9u4/Oq7yvBf999l7z4xGI4FkIbnBMjZQx4T2yOCZk6bQk0WgpbSQkhwZSotqmuSY2G5Iji/Xgduec5J70q4FuNSXH0Uqzo/imp4UrOaGlbSULCiHm9KTRjLYzSEYhx9GIqklxjJIo5Fm9t7v/WNmb8+PPaORNKM9M/p+1tKSZu937/fdo1fPPB7ved7vvILbrrhwwVJXgYCOdZ2t2NAVwboKk2paWbadWYDCa/5Nz1vufZ4A0BrUMT6VxNDzr+Pe/vw5NDgQxfDoWN7jv3j+dfdxKKA1xYs1+SNlK7eeNJCJdXueOIpUDd89FkHRPK91iT8gU5bSq98aV/lrOrwVhKhJdIYD+Pw1Hyy6X7rcLRA9bSEMDUSLjulpK/3f3UaJDxQaC5Tbmzdt3Pf08bz79+57+jgeuOWy0n1pGh57MX9xhsdefBN//Il/V7Yvqm/OvdX7v3e8uC70QBQhQ/Lm15lk2q3I4ZTK64oE0dEahFI27v6ND+Hu3/gQArqG95Npd2nyfdv6MDNn4ryIYlJNS1LqtoxaVujQS8S9r9Q47mkl+v2TT/bVtN9mw8SaqElMJdOe90uXu8da0wStwfya1K1BvWwSYpT4QOFCJZlChobJmXm3VBngVN0ofdx5bSHs+dXN2PFXOR9q+b0YziuT+FP9y723uiMcxMFPfxinEynEEyk88Oxr+C/XX5r3j7eh519359xLY2fwle9kFmrZ++RRTM7M4ys3/iJaAhq620OYTVnu0uT3PX0ckzPzrEVOSxYoURWk3C1syxUyxPNNklovmNIVCWLPr23mB7iXiYk1UZNYyj3W8UQK27/+L0UvGuUSkbTl/c7zw797ednxCYAHbrkMX/jmy27QfuCWy1DupULTBJt/rnk+1EIZuXP1mkvXFs1BAHmrZ07OzOO8tiD+5vaPYGJ6HhPTmUVenCXJL+6OoK3FQNq08at/9oJnf0RLsdSVZpcjMW/hwYLqHA8++xq+9PFfQEdr7fpttg8R+oWJ9Sqy8e7vLqr9W/dcX6ORUC0spQ7zUpLxoKGXeOe5/H3M85aNP/7Oj/NeLP74Oz/GA79TPiFnJYbmkztXO8LFi7w888oE7rh6E+75j/8OP3duC3QR/Nv7c9iwxnDLKDp6O8MIBw2siYTcRVxYi5yqxVbA177/Rl7c+tr336jpqoB+LpjCeLt8/PAiUZNw6jDnfvBkof/GcxKcXAslIkvpB8gsAuAk5LkVHBp1EQBautw55Nw/nctZ5GXga/+CX/2zF/Cx+/8n9h4+hpagXnbuLXVuEpUSCen43NWb8j5A/bmrNyESqt0/1pwFU3I18oIpq42oMksDNzIRuQ7AAwB0AF9VSt1Trn0sFlMjIyNlz7nYd3wbHd+x9uT7/4mVm6uLXXlxKYvKLKWf5fRFS+brk7pQTHXmkG3beDeRwmf/ajRvXoQMzb1FJHeuACg795YyN8lXvv9yFoqp75yZxbyp3DrWIUOwrqO1ZvOKsbJuVfTkN+WtICKiA/hzAL8GYBzAD0XkKaXUK/6OjKi2FvvfeEu9p26pi2vw/j1y5M6h7vaWonkBoORcKTf3+F/ZVE2alkmiV/Ifa4yVja0pE2sAHwbwE6XUGwAgIt8EcCMAJtZEBVYyEWHSQ15KzQvOFaoHfsQtxsrG1aw37KwDMJbzeDy7jYiIiIioJpr1HWuv/y8puplcRG4HcDsAXHDBBbUeU8NhFZH6wblKjYDzlBoF5yrVSrO+Yz0OYH3O414APy1spJR6VCkVU0rFuru7V2xwRIvFuUqNgPOUGgXnKtVKsybWPwSwSUQuFJEggFsAPOXzmIiIiIioiTXlrSBKKVNEPgfgH5Apt/d1pdT/9nlYTa/RyxHyVhYiIiJajqatY71YIjIJ4GT24XkA3vVxOJVqhHE2whiBysf5rlLquloPppyCubqaNMpcqrWGmKs587QRf28c88o4D8CrDRRTG/E5XqrVdK1AZddbUUxlYu1BREaUUjG/x7GQRhhnI4wRaJxxrmb8HWU02vPQaOMFOOaV0mhjbrTxLsdqulagutfbrPdYExERERGtKCbWRERERERVwMTa26N+D6BCjTDORhgj0DjjXM34O8potOeh0cYLcMwrpdHG3GjjXY7VdK1AFa+X91gTEREREVUB37EmIiIiIqoCJtZERERERFXAxJqIiIiIqAqYWBMRERERVQETayIiIiKiKmBiTURERERUBUysiYiIiIiqgIk1EREREVEVMLEmIiIiIqoCJtZERERERFXAxJqIiIiIqAqYWBMRERERVQETayIiIiKiKmBiTURERERUBUyss6677joFgF/8WujLd5yr/Krwy1ecp/yq8Mt3nKv8qvCrIkyss959912/h0BUEc5VagScp9QoOFepmphYExERERFVARNrIiIiIqIqYGJNRERERFQFTKyJiIiIiKqAiTURERERURUYfg9gOUTk6wBuADChlPrF7LY1AP4GwEYAbwG4WSk15dcYS7FthXgihZRpIWjo6AwHMJVMu4+7IkFomlStDxFBUBekLAWllGcfpmljYmYeactGUNcQDAjmUnbR+HLPpQsgIkhbNkxbIaAJWoI6OsILj7/wOVjomhfbfrHPjy6ApmlVee6JqH6ViiW2rfBuYh7zaQuaCEQAQNDTFoKmCd5NzGMubUHP7hMIurP7ysXzpcZ321Y4k0whmbJgKYWWgI7zIqGK49NCrzO1eN3x6pcxtXHk5gEBXUNPWwiGUfv3YOfmTMSTKZi2gqEJusJBtLQ0ZoramKM+6y8BPAzgYM62uwE8q5S6R0Tuzj6+y4exlWTbCsdPTWPHwRGMTyXR2xnG0EAUDz77Gp55ZQK9nWEc2B7D5rXtSw5GXn08cutWPPzcCc8+TNPGq6emsfPQqNt+37Y+3Pf0cUzOzOeN79pLe/C5qzfh4edOYPfHfh7JlIW9h4+5x+2/eQu62kLY2BUpOX6v8ZW75sW2X8rzc29/Hx578U3s+bXNy3ruafk23v3dRbV/657razQSajalYsmm7jacmJzxjAmfv+aDODds4HcO/KBo3xevuwRpU2HHX5WO50uJ77at8FY8gVPvz+XF10rjXuF1XntpDz5/zQfzYny1X3fKPb+MqfXPKw8YGojikrXtNU2u5+ZMnIgnsCun38GBKDZ1RRoyuW7oW0GUUi8AOF2w+UYAj2V/fgzAJ1Z0UBWIJ1Ju0AGA8akkdh4aRX90vft4x8ERxBOpqvax+/EjJfuYmJl3/5ic/XsPH8POqy4uGl9/dL17rqlE2g36znF7njiKk/HZsuP3Gl+5a15s+6U8P3cNH0N/dP2yn3siql+lYsnEzHzJmLDz0CjmTeW5b+x00k2qnX2F8Xwp8T2eSOFkfLYovlYanwqv07mOWr7uePVbrfNS7XnlATsPjWJiZr6m/caTKTepdvrddWgU8WRjzpmGTqxLWKuU+hkAZL/3lGooIreLyIiIjExOTq7YAFOm5U4gx/hUEh3hQN7jlGmtWB9pyy7bPvfnjnDAfdwa1D2Paw3qZcdfanyljlls+4WUe36W+9zXgl9zlWgxGmGelvrbLxcDx6eSKHyzdaEYWBhrFxvfU6ZV8tyVxKfC63SuY6FxLjf2VTtW10ojzNWVVupvwLTsmvZr2sq7X7vixQ7rSjMm1hVTSj2qlIoppWLd3d0r1m/Q0NHbGc7b1tsZxplkOu9x0NBXrI+ArpVtn/vzmWTafTybsjyPm01ZZcdfanyljlls+4WUe36W+9zXgl9zlWgxGmGelvrbLxcDezvDKHyNXygGFsbaxcb3oKGXPHcl8anwOp3rWGicy4191Y7VtdIIc3WllfobMPTapoqGJt79NuitQ82YWJ8SkQ8AQPb7hM/jKdIVCeLA9pg7kZz7mIZHx9zHB7bH0BUJVrWPR27dWrKPnrYQhgaiee33bevD0POvF41veHTMPVdnJIB92/ryjtt/8xZs6GotO36v8ZW75sW2X8rzc29/H4ZHx5b93BNR/SoVS3raQiVjwtBAFCFDPPetXxPGgd8rH8+XEt+7IkFs6Gotiq+VxqfC63Suo5avO179Vuu8VHteecDQQBQ9baGa9tsVDmKwoN/BgSi6wo05Z0Spxnyr3SEiGwF8J6cqyD4A8ZwPL65RSn1xofPEYjE1MjJS07HmqueqIGb208CLrQpiZT/N2+RVQXz/J/RKz1U/8MOLVeHrXK3nebpwVRAbmsCzKohTMUTL7lu5qiBAS0BrxqogjKl1JDcPMFgVpFBFc7XuRr0YIvI/AFwF4DwRGQfwJQD3AHhCRD4D4G0AN/k3wtI0TdDdnv+vwMLHteijHMPQcH5H/n/HIHL2R7/Ht9j2K30+ImoMpf72NU3Q095S8rhy+xaK50uJNZomWBMJ5cXhxR5fi3EtpV9qDJ55wApoaTGwrv4S6SVp6KtQSv1OiV3XrOhAiIiIiGjVa+jEmogI4K0jRERUH5rxw4tERERERCuOiTURERERURUwsSYiIiIiqgIm1kREREREVcDEmoiIiIioClgVpIEUFt3vaDEwmUghbdkwNEE4qGEufXYBmM5wAEkzhemkjXS26LqhCeZNG7omCOgCQGDZCroGpC3lFmdvCWiYmbcQ0DWEDHF/7o4EMZ0yswsWKLQE9LwFC3LHGDA0GJogmSq9SEAlC+UAqOrCMES0ejiLvsylLbQGdKRMG6atEDI0mPbZmBcyNFjZx862gKEBtkIyGzPDhoZ5S7mLZ3RHgjgzZ8K2M+e0lIIuAhHAkMwKM2nLLoqV1V7siqha/FqopUEWiKlIY456FbJtheOnprHj4AjGp5Lukp8PPfsannllwvPx3+7+ZUy8n8LOQ6PuMfu29eG+p49jcmYegwNRaFB46uV3cP2Wddj9+BG33SO3bsWhfz6JF9+Iuz+fSaaw97pL8O70PPYePua2PbA9hs1r2wGgaIy5/TntcpPwwvZDA1E8mHMNBz/9Ycybdl6bwvMQEXnJjTFXXNSFgV/egN2PH0F3WwhfvG5zXhwbGohCoPDZQ0fy4ldrUMeXn3oFkzPzeOTWrXj4uRN5Mfc7L4/jo5vX4q7hs+e6/6Yt6Gg1cDqRLoqVm7rbcGJyhjGN6s7cnIkT8QR25eQMgwNRbOqK1DTJ9avfWuGtIA0inki5gRgAxqeS2HVoFP3R9SUfp0zlJtXOtr2Hj2HnVRe77SemU9gWu8BNqp12ux8/gh0fvSjv5/7oeoyfTrovFE7bHQdHEE+kPMeY25/Trtw17Sy4hpPx2aI2hechIvKSG2N2fPQiN87tvOrioji2MxsPC+PX6UTajWG7Hz9SFHO3xS5wk2pn+51PHoWu6Z6xcmJmnjGN6lI8mXKTW+DsHI8nazs3/eq3VhrvnwKrVMq03EnnGJ9KoiMcKPnYslXZY8ankmgN6tA18WynZ989cX7OPa6wbcq0Su7LPc5pV+k1tQb1sv0REZWSG2Ny41xHOOAZV1qDuue2Vuju48KYWyp+auIdD03LZkyjumSWyBlMWzVlv7XCd6wbRNDQ0dsZztvW2xnGmWS65GNdk7LH9HaGMZuyYNnKs52VndTOz2eSacymLM+2QUNfcIxOu8VcU7n+iIjKyY0xuXHuTDLtGVdmU5bnttwYVhhzS8VPW8Fzu6FrjGlUl4wSOYNR41uU/Oq3VphYN4iuSBAHtsfcyefcgzQ8OlbycdAQDA1E847Zt60PQ8+/7rbvaQ/i8MjbeOTWrXntHrl1Kw688Ebez8OjY+hdkzlHbtsD22PoigQ9x5jbn9Ou3DUNFVzDhq7WojaF5yEi8pIbYw688IYb54aef70ojg1l42Fh/FoTCbgx7JFbtxbF3MMjb+Pe/vxz3X/TFli25Rkre9pCjGlUl7rCQQwW5AyDA1F0hWs7N/3qt1ZEqcZ8q73aYrGYGhkZ8XsYZZWqCmJa2U+sV7kqSGLegpGtCuL8nF8VBGgJaKutKojv/4RuhLm6XBvv/m5Nz//WPdfX9Px1wte5Wi/z9GxVEButAa2oKkgm/uVXBXG2LbUqiCaAnlcVJD9WsipIHt8vvF7maj1gVZCyKpqrdTdqKk3TBN3tobxt53eES7TOaDda0N6ytP662rx/XhPQgUjlYyzVtlT7ouNLbCMiWoimCXqWGgQr0B1Y/C0cnnGSqA60tBhY50NC61e/tcBbQYiIiIiIqoCJNRERERFRFTCxJiIiIiKqAibWRERERERVwMSaiIiIiKgKmFgTEREREVVBc9Q28SAiewD8JwAKwL8C+JRSam6lx1GuTrOmCXQRJNNWpmaqJrCVgq0ATQBbZVYkChqClKmgaeLWYA1oAsPQMjWidQ26JjBtG0plVhgL6BpEMkUXdU2QSGX6aDE0pCwbaUud7RMKGsStwxrS8+u7ahoAlanNOmfabj3sgKGhI7z4+qus4Up+W2yd7FVS97rh5NXN1zVAZWKYnY2DLYYGSwEpy0Y4oMG0gXS27n8gG3NEMjX8nZhr2QpBQ4NtK5g5daltBQR0cdsqlVmKWcvGQwHc+N0a1JBMZWK1rkk2Fgu62zJ1rOOJFGzbhmTrXDvtwkEN54aCRbX8GR/95cdrll+vk6xjvXyNOeoFiMg6AJ8HcKlSKikiTwC4BcBfruQ4bFvh+Klp7Dg4gvGppLu614PPvoZnXplwV/a67+njmJyZx75tfQgHdTzyjz/BbVdciMdefBP/7eOX4v2EDdu2MW8q7H78iHuu3GP//Hcvx1zaxp1PHnX3P/Q7l0MTIBzU8dUX3sSZZAqfu3pT0Tk6IwFMJ03seeIouttC+OJ1m7H38DG3zb39fXjsxTfxqSsvdPvbf/MWBA0NZ1rS2NgVqfgP3us5ObA9hs1r2/niQUQV84oluXGwuy2E/3LDh/CFb76M7rYQ/vA3L8GeJ47mxb7u9iCSKRsPPXcCt11xIe4aPlYyBr5w/BSu37IODz93Ap/5lYvyYu2+bX1oDepQAP7+2E/x8ct6sfPQaFEM/fw1H8S5YQNf+c4ruOPqTZhLW3lj2n/zFnRG0vj9b/yQ8bFO+PGa5dfr5NyciRPxBHblzN3BgSg2dUVqmuT61W+tNPOtIAaAsIgYAFoB/HSlBxBPpNw/DAAYn0pi56FR9EfXu4/3Hj6GnVdd7P48lUijP7oedw0fy7YTjJ9OQtd0NyH2OvZ0Iu0Gemf/Hf/jJZxOpPHO1Bx2fPQi9EfXe57D0HQ3uO+86mL3BcVp44wlt789TxzF6UQaJ+OziCdSy3pOdhwcWdQ5iIi8YkluHNx51cX4wjdfdn92YpzTdu/hYwA07Hr8iBtzy8XAbbELsDvbtjDW7j18DKcTaUwl0tgWu8BNqnOP74+ux85Do5g3Ffqj6/HuTKpoTHueOIqx00nGxzrix2uWX6+T8WTKTW6dfncdGkU82Zz91kpTJtZKqXcA/CmAtwH8DMB7SqlnCtuJyO0iMiIiI5OTk1UfR8q03IniGJ9KoiMc+4ghiQAAIABJREFU8Hw8PpVEa1BHRzjgbrdshdagDk1Q9lytQd1zf2tQR2tQh66Je97CNrnnLtUmd0yF506Z1rKfk8WcYzWq9VwlqoaVnKdesSQ3DubGsoViXyVtdU2K2ubuz4215WKoJpk+ysXswm2Mj9VX6Vz14zXLr9dJ01ae/Zq2asp+a6UpE2sR6QRwI4ALAZwPICIiA4XtlFKPKqViSqlYd3d31ccRNHT0duYvOd7bGcaZZNrzcW9nGLMpC2eSaXe7rglmUxZshbLnmk1ZnvtnUxZmUxYsW7nnLWyTe+5SbXLHVHjuoFH5kr6lnpPFnGM1qvVcJaqGlZynXrEkNw7mxrKFYl8lbS1bFbXN3Z8ba8vFUFtl+igXswu3MT5WX6Vz1Y/XLL9eJw1NPPs1anwbkl/91kpTJtYAfhXAm0qpSaVUGsDfArhipQfRFQniwPaYO2Gce6yHR8fcx/u29WHo+dfz7nceHh3Dvf192XYKvWvCsGwLj9y6Ne9cuceuiQRw/01b8vY/9DuXY00kgHWdLTjwwhsYHh3zPIdpW9h/c+bYoedfx75tfXltnLHk9rf/5i1YEwlgQ1cruiLBZT0nB7bHFnUOIiKvWJIbB4eefx0P3HKZ+7MT45y2+7b1AbAxeOtWN+aWi4GHR97GI9m2hbF237Y+rIkE0BkJ4PDI2xgaiHrG0KGBKEKGYHh0DOe1BYvGtP/mLVi/Jsz4WEf8eM3y63WyKxzEYMHcHRyIoivcnP3WiijVmG+1lyMivwTg6wD+PYAkMh9aHFFKPVTqmFgspkZGRqo+lkqqgsylMz87FTpsG9A0wLazVUECglTauyrIXCrzaXhdE1i27X6qvbAqyGwq04dTFcS0VF6flVYFmTczn6hfxVVBfB9oreZqPVls1Y5aa9CqIL7O1ZWYp55VQbIx1FIKLXqmKkjastGyUFWQbMy1lEJQz1QFsZSCJuLuW7AqSLZvtypITlURlKkKYmXPs0qrgvh+cQvNVVYFYVWQrIp+AXU36mpQSv1ARA4DOALABPASgEf9GIumCbrbQ3nbCh+vNl7PCRHRYtVzLOmMlN630Jjr9ZpWKz/mmV9zu6XFwDofElq/+q2F5rgKD0qpLwH4kt/jICIiIqLVoVnvsSYiIiIiWlFMrImIiIiIqoCJNRERERFRFTCxJiIiIiKqAt8/vCgi0wC8av4JAKWUOmeFh0REREREtGi+J9ZKqXa/x0BEREREtFy+J9aFRKQHQIvzWCn1to/DqUipQu62rXAmmULatJG2FXQBbAVo2e+WrdBiaIAIbKXcRVkCWmZlF00yiw5YSkFl2zuLs8ybNjRNzi5EkC2q3hLQYNlAMm1B1wRBXYNSmYUODC2zOIzltA1q6AyH3LG+m5jHXNqCLoJwUF/S4i9ERNXkFZvOCWUW2rJs212xQSETI81snHQXw7Izi7Q4i7s4cddUCmkrEwsNTTBv2dBFIAIYWuYuSSdeBvTMYl4BQzCXjbd6dkGX3MfOedxFtpRCS0DHmvDZRV/CQR2mrZA2bQQMDYYmSKaKXzsaeBGtpuPH72O1LdTiV7+maWNiZh5py0ZA19DTFoJhLO8u6bpJrEXktwDcD+B8ABMANgD4MYBf8HNcC7FtheOnprHj4AjGp5Lu0qObutvw9tQspufSmE1Z+MY/vYnbrrgQj72Y+X7X8DF0t4Xw5d+6FAAwm7Kw9/Ax9xz337QFX/v+G9jxHy5CwNDwub9+yd23b1sf7nv6OD68sQM3XNaLXYdG3X2P3LoVIUNw9/CPMDkz7y61a9rA+8l0Xh/7b96CrjYTF3S24sTkTN417NvWh7XntGBjV4QBnYh84RVf//x3L4euaXjw2dew+2M/j4CWWTU2ZdrY88TRvFj48HMn8MwrE3mPJ6dT+OJ1m/NioRNTJ2fmcf9NW9DRauB0Ij9ePro9CtsGdubE28GBKB569jW3j33b+vCtI+/gk1vX5R07NBDFg8++tmDfzmtHYTw+sD2GzWvbGYt9UOo1vpa/j7k5EyfiibzX9sGBKDZ1RWqabK62fk3TxqunpvP+pocGorhkbfuykut6+vDiVwB8BMBrSqkLAVwD4J/8HdLC4omU+wcHAONTSew4OIKJmXmcjM+6wbk/uh53DZ/9Pj6VxM6rLsbpRDovgDvnuPPJo+iPrseeJ45iKpHO27f38DHsvOpibItd4E5EZ9/ux49A13TsvOpit62u6Zh4f76ojz1PHMXJ+CwmZuaLrmHv4WM4GZ9FPJFa6aeUiAiAd3w9nUhj56FR9EfXYyqRxsR0CqcTaTepdtrtfvwI+qPrix7vvOrioljoxFQn9uqaXtTm1Hvz7guws21Xdhy559nx0YuKjnXGu1DfzmuH12sKY7E/Sr3G1/L3EU+mil7bdx0aRTxZ2zmw2vqdmCn+m955aBQTM/PLOm/dvGMNIK2UiouIJiKaUuofReRevwe1kJRpub8Ux/hUEmnLRmtQdx93hAN53wGgIxzIO6bwHE5b5zyF+3RNPI/T5Oy5ncetQd2zbWtQh2nZJfelTGuxTwkRUVV4xVcnluXGT6B0DPV6XK6tEzNL9btQH6XicqV9p0vEY8Zif5R6ja/l78O0lWefpu1V54H9LlWpvzXTspd13np6x/qMiLQBeAHA4yLyAADT5zEtKGjo6O0M523r7QwjoGuYTVmYTVno7QzjTDKd9x0AziTTeW0Kz+G0nU1ZnvssW3keZ6vMuXMfl+pjNmXB0LWS+4JGflJPRLRSvOJrbkx14me5GFr4ODcGe7V1Ymapfhfqo1RcrrTvQIl4zFjsj1Kv8bX8fRiaePZp1PhWoNXWb6m/NUNfXmpcT4n1jQCSAPYAeBrA6wA+7uuIKtAVCeLA9pj7y3Huv+ppC2FDVyvWRALYt60Pw6NjuLf/7PfezjCGnn8dayIBt03uOe6/aQuGR8ew/+Yt6IwE8vbt29aHoedfx+GRtzE4EM3b98itW2HZFoaef91ta9kWes4JFfWx/+Yt2NDVip62UNE17NvWhw1dreiKBFf6KSUiAuAdX9dEAhgaiGJ4dAydkQB62oNYEwlg/81bimLh8OhY0eOh518vioVOTHVir2VbRW3WnhvCUEG8HcyOI/c8B154o+hYZ7wL9e28dni9pjAW+6PUa3wtfx9d4WDRa/vgQBRd4drOgdXWb09b8d/00EAUPW2hZZ1XlKrtW+2NIhaLqZGRkSUdu+iqIBpg295VQezsJ2JFAFlGVZC5tAUtpyqIrRT0bFUQ2/nUvGdVEBu6gFVBSvP9CVnOXG0UG+/+rt9DyPPWPdf7PYSl8HWuVmueesWmclVBLFtBq7AqiGnlV/PQRaAJoOdUBbFtBYNVQWrJ9wtbaK6yKkjz9utUBTEtG8bCVUEq+qXXzT3WBQvFBAEEACQaYYEYTRN0txf/C0fTBGsiy/uXT0Uiyz+Fpgl62lsWbkhEtIJKxSavmLsiCuNthfG37HgLzlHqNYX84cfvo6XFwLoVSCxXe7+GoeH8jvDCDRdzzqqebRkKF4oRkU8A+LBPwyEiIiIiWpR6usc6j1Lq/wVwtd/jICIiIiKqRN28Yy0i/zHnoQYghrO3hhARERER1bW6SayRXwHEBPAWMpVCiIiIiIjqXt0k1kqpT/k9BiIiIiKipaqLe6xF5EYR+ScROZ39ekZEfiW771y/x0dEREREtBDf37EWkd0APg3giwCcQpIxAPdlV1/8QwBblnDeDgBfBfCLyNyr/Wml1D9XZdA5TNPG9HwKc2mFlGVn6kMbGtKWgq4BpqUAAZSCW0taF2DOtGFk61DPZuugBjSBrgnmTBvhQGap8XS2pqOmAVCZGqtzpu22nTdthIxMzVTTVgjqGrrL12EkIqp7tq0wlZyHbQO6BiRTNkQAQJDOxtqAJhANSJsKLQENc+mzNf0jIQ2ptELKVtAEgAIku5ZAbq3rtK2QMs+eT9cEhg4kU5mYbuTUpzYk87OZXVtA0wANgnS2fnZA1wAohAwNlgLSpg0RgS6ApmkL1j9eZfWrG4YfNZZXWz3pdNrK1JPO9tvTFkIg0JirjfqeWAO4A8CVSqnTOdueE5GPAxgH8H8s8bwPAHhaKbVNRIIAWpc5ziKmaWMyMYfTM2l89tAoxqeSuPbSHnzu6k347tF3cMOWdXjouRO47YoLcdfwMYxPJd2Vtu57+ji624O445oPYlf2WGfft468g09uXYe9h88ec29/Hx578U186soLcd/TxzE5M1+y7dBAFJesbWdyTUQNybYV3oonkLYstAYNTM2m8fBzJ/CZX7kIdz55NC9edrUFcfxn72Fj9zl5sXRoIAqBwgPPZmLwYy++WRSLB2/dioeeO4FnXplwz/eBjhbMzFnYWRCXnbi7/+YtCBgaHvnHn2D3x34eyZSVF38fvOVy6BrwB3/9UlH83vNrm7F5bbtnsmzbCsdPTWPHwRH3uAPbYyXb08qYmzNxIp7Im1uDA1Fs6orULOH0o08/+02nLbw6MVPU7yU9bQ2ZXNdF5lWQVDvb4gBOKqUGF3s+ETkHwEcBfC17rpRS6syyB1ogs1oP3KQaAPqj67H78SPYFrsAux4/gv7oejeQA8D4VBJ7Dx/DzqsuRn90vTuRcvft+OhFbqB2tt81fAz90fXuseXa7jw0iomZ+WpfLhHRiognUjgZn4Wu6Zg3FXZnY6mTVANn4+U7U3O4fENXUSzdeWgUE9MpNwZ7xWInRueez7TgJtW52524u+eJo5hKpNEfXY+pRLoo/n7+my/hdCLtGb93HBxBPJEqec1OUu0cV649rYx4MlU0t3YdGkU8Wbvfix99+tnvxMy8Z7+NmsfUQ2L9vogU3eqR3fbeEs95EYBJAN8QkZdE5KsiUrQ+lojcLiIjIjIyOTm56E7Slg1LKXcyAEBHOIDxqSR0TTA+lXQf53K2l9rnHOt1jPN9obamZS/6eqh+LXeuEq2Eas3TlGmhNahDE0ATlI2lrUEdlq1K7suNm6Xiau5jp79S7XLP2xrUS/brdfz4VBIp0yp5zV7nKtWelqfSuWqWmFumXbtqwH70uRr7rZV6SKzvBPCUiHxZRD4uIjeIyP8N4NvZfUthANgKYFApdTmABIC7CxsppR5VSsWUUrHu7u5FdxLQNegi6O08uxzmmWQavZ1hWLZCb2fYfZzL2V5qn3Os1zHO94XaGno9/GqpWpY7V4lWQrXmadDQMZuyYKvMPdHlYulsyoKuScl9uXGzVFzNfez0V6pd7nlnU1bJfr2O7+0MI2h4/9d20NA9z1WqPS1PpXPVKDG3jBrenuNHn6ux31rxPftSSn0fwC9lx/L7yHyQUQPwkey+pRgHMK6U+kH28WFkEu2q6mkLwdCBvxiIupNieHQMj9y6FYdH3sbgrVsxPDqGe/v73P3O/XpDz7+O4dExDOYc6+w78MIb2Lct/5h7+/swPDrmHluu7dBAFD1toWpfLhHRiuiKBLGhqxWWbSFkCB7JxtL7b9pSFC/XdbbgpZPxolg6NBBFT3vQjcFesdiJ0bnnM3RgyCMuO3F3/81b0BkJYHh0DJ2RQFH8ffCWy7EmEvCM3we2x9AVCZa85gPbY3nHlWtPK6MrHCyaW4MDUXSFa/d78aNPP/vtaQt59tuoeYwo1ZhvtS9ERP4/AP9JKXVcRL4MIKKU2luqfSwWUyMjI6V2l5RbFSRt2Wc/ab6MqiDzpo2WbFUQ01bQK6wK4nwqnVVBasr3f0Ivda42ko13f9fvIeR5657r/R7CUvg6V5c7T8tVBTGzsbbSqiB6NgaXqgqSNs+eL7cqiFN9xNAkU/WpTFUQ21YwdA0ChSCrgiyG7xe40FxlVRBWBcmqaK76XhVERP4V3kuXCwCllOpb4qnvAPB4tiLIGwBqsgCNYWjoNFqWdY7Ooru/iYhWN00TdEVyYusKx8mOqteRWpimCbrbG/NdumbW0mJg3Qokl3736We/gYCOdZ0+/NHVgO+JNYAbanFSpdTLyNTDJiIiIiKqOd8Ta6XUSb/HQERERES0XL4n1iIyjfK3gpyzwkMiIiIiIlo03xNrpVS732MgIiIiIlou3xPrQiLSA8D9xIpS6m0fh0NEREREVJG6qckmIr8lIicAvAngfwJ4C8Df+zooIiIiIqIK1U1iDeArAD4C4DWl1IUArgHwT/4OiYiIiIioMvV0K0haKRUXEU1ENKXUP4rIvX4Pyotp2jg9m0LKsmHZCue06JhN2bCUgi6ZRVwgmcUG5s3MggUhQ0NAF5iWQtpdzEWgiUAA6NmFDuZSZxc4aAloMC0FSynYKrPspyaCNa1BLgBDRE3JNO3sQhGZBVlaAhrmzbOLtQSyC6aEg4LpuUwM1rVM3BUR2Ar5C8hkF4fJjbu6COYtGyFdg62QWfwluxCME481De7CX0b2PJoINAApZ0EYTdAS1NEeNPBuIuWeJxzU0BkOeS7uskoXgWloXCCmefutxd9jPSXWZ0SkDcALyCzsMgHA9HlMRUzTxlunE5icnsfew8fw29FeXPWhtdh1aBTjU0l3+drHXnwTd1y9CQ89dwKT0ync0/+LEBHEZ1LYe/iY2/aBWy7LrsCoQ0Tw+9/4obvvkVu3IhLSMT1n4pF//Ak+deWFaA3qeH8ujY1rIkyuiaipmKaNV09NY2dOPB0ciOKhZ1/DM69M5C1jPnHayou7D//u5UibNvY8cdTdtm9bHz7Q0YLJ9+fztu+/eQueHBnHTbHeovatQR3hoI5QQMeffOcVt9/7b9qCjlYDpxPpvBj+6PYofmojb8z7tvVh7TkmNnZF8l6kbVvh+Klp7Dg44rY9sD2GzWvbmVzXqbk5Eyfiiby5NjgQxaauSM0SPz/6XI391urvsZ4ysxsBzALYA+BpAK8D+LivI/IwMTOPsdNJN7DeuLXXnQwAMD6VxF3Dx9AfXY9djx9Bf3Q9dl51MXRNxztTc+5xTtsvfPNlnE6kMT41h7HTybx9ux8/AqUEU4k0+qPrsffwMZxOpDF2OomJmXnfngMiolqYmJl3E1QgEwd3HRpFf3S9+3jv4WMQaEVxdyqRdpPk3LamhaLte544ih0fvciz/elEGu9MzSFtqrx+73zyKHRNL4rhp94rHvPew8dwMj6LeCKVd33xRMp9EXfa7jg4UtSO6kc8mSqaa7sOjSKerN3vzI8+V2W/Nfp7rIt3rEVEB/BtpdSvArABPObzkEpKWzZag7r7i7CVcn92jE8l0REOuN8BQBPkHZfbtjWoe/Y1PpV0j2uFntfWtOxqXxoRka/Sll0ynuY+tjzibqn4qgk8t+ualI3HmqCoX69zlYvrKdPK254yLc+2he2ofpi292u8aXstv9G4fa7Gfmv191gX71grpSwAsyJyrt9jWUhA1zCbstDbGQaQuefO+dnR2xnGmWTa/X4mmYatkHdcbtvZlOV+Fe5zjnPO57Qz9Lr41RERVU1A10rG09zHukfcLRVfbQXP7ZatysZjW6GoX69zlYvrQSP/TZOgoXu2LWxH9cPQvF/jjRreuuNHn6ux31r9PdZTdjYH4F9F5Gsi8qDz5fegCvW0hbB+TeYeut7OML59ZByDA1H3l+PcYz08OobBW7dieHQMQ8+/Dsu2sK6zxT3OafvALZdhTSSA3s4WrF8Tztv3yK1bIaLQGQlgeHQM+7b1YU0kgPVrwuhpC/n2HBAR1UJPWwhDBfF0cCCK4dEx9/G+bX1QsIvibmckgP03b8nbtm9bHwwdRdv337wFB154w7P9mkgA6zpbEDAkr9/7b9oCy7aKYvjac4vHvG9bHzZ0taIrEsy7vq5IEAe2x/LaHtgeK2pH9aMrHCyaa4MDUXSFa/c786PPVdlvjf4eRanavtVeKRG5zWu7UmpFbguJxWJqZGSkora5VUFsW6F9gaoglq0QLKgKYtsKRoVVQWylYLEqSL3w/RNGi5mrjWrj3d/1ewh53rrner+HsBS+ztWlztOqVAWxbWhSXBXEibuFVUHS2SoiXlVBzGy/zvnLVQVxzsOqIIvi+8UvNFdZFaR5+13k32NFc7Uu7rEGMgm0iIQBXKCUOu73eMoxDA0957TkbeuMVOnk1ToPEVEDMgwN53eEF24I4JzKmq2ID1Q4Zk0TdLfzfxwbSUuLgXUrkOT53edq7LcWf49187aniHwcwMvIVASBiFwmIk/5OyoiIiIiosrUTWIN4MsAPgzgDAAopV4GcKGfAyIiIiIiqlTd3AoCwFRKvSeSdwtLfdwATkSr2mLu+W7Q+7GJiKgK6imx/pGI/C4AXUQ2Afg8gBd9HhMRERERUUXq6VaQOwD8AoB5AH8N4D0A/9nXERERERERVaie3rHerJT6IwB/5PdAiIiIiIgWq54S6z8TkQ8AeBLAN5VS/3u5J8wulT4C4B2l1A1LPY9tK7ybmMdc2kJbSEcyZbu1UW2loIkgZGiYMzN1rQN6pma1U8M6tz5qKCB4L2khZGhF9VYDhoaOcGU1TVkLlYiaiRPTQgGF5HwmbqbMTF3/gCZoCWpIps7WrXZisKYBtg33cUAXGLogmbMmQGtQw2zKRkAXpC0FTTIf4Elbyq2NvaY1CF3XiuIqAMQTKdi2DUsBSinG3FWGdazrrp501Th189OWjYCuoacttOx1QuomsVZKfUxEfg7AzQAeFZFzAPyNUuqPl3HaLwD4MYBzlnoC21Y4fmoaOw6O4LejvbjqQ2vx0LOv4bYrLsRdw8cwPpV0V0l8+LkTeOaVCVx7aQ/uuHoTdj1+xN2/b1sfWoM6WkMG3pqcQVtLAHsPHyvaf6YljY1dkbITKndMzvEHtseweW07Az0RNRwnpiXnU2hvDcG2bcybCruzMfSz/2EjbrisF7sOjbox797+Pjz24pu47YoL877/0fUfwvvTVl7bwYEopmaS6Ii04OHnTuAzv3IR7nzyaF78nW43oUGw/Rv/khdXQ4aGe/7+x0UxnzF3dZibM3EiniiaT5u6IjVLOP3o089+/cppTNPGq6emsTPneocGorhkbfuykut6uscaSql/U0o9CGAnMjWt/9tSzyUivQCuB/DV5Ywpnki5v+wbt2YCe390vRtgAWB8Kondjx9Bf3Q9AKA/ut5Nqp39ew8fw+lEGuOnk7j0/HPdpLpw/8n4LOKJVMVjco7fcXBkweOIiOqRE9PWntuK8dNJ6JruJtUAsC12gftiD2Ri3l3Dx9xYnPs9baGo7a5Do7i45xw3TjtJtbN/7+FjGDudxMnTs0Vx9WR81jPmM+auDvFkynM+xZO1+9370aev/fqU00zMzLtJtdPvzkOjmJiZX9Z56yaxFpEPiciXReRHAB4G8M8Aepdxyv8HwBcB2GX6vF1ERkRkZHJy0rNNyrTcJ91WCuNTSXSEA+42h7MdQMn9rUEdrUEdpq3K7k+ZVtkLyx1T7vELHUeNq5K5SuS3pc5TJ6aZtkJrUIcmyItxuiYlY27h98JjnbZO3F0oPnttL3UMY27jqnSulnq9Nu3aVQP2o08/+/Urp0lbtvf1WiXTxorUTWIN4C8BWAB2Afh1pdQjSqmJpZxIRG4AMKGUGi3XTin1qFIqppSKdXd3e7YJGjp6OzNL1Woi6O0M40wy7W5zONsBlNw/m7Iwm7JgaFJ2f9DID+7lxpR7/ELHUeOqZK4S+W2p89SJaYYmmE1ZsBXyYpxlq5Ixt/B74bFOWyfuLhSfvbaXOoYxt3FVOldLvV4bNbxFwY8+/ezXr5wmoGve16svLzX2PbEWEUNE7gNwMYBPAngQwJiI3CcigSWe9koAvyUibwH4JoCrReTQUk7UFQniwPYYejvD+PaRcQwORDE8OoZ7+/vcX4hzj/Xw6BgAYHh0DIO3bs3bv29bH9ZEAuhdE8YrP30P+7b1ee7f0NXqfmCmkjE5xx/YHlvwOCKieuTEtFPvzaJ3TRiWbeGRnBh6eORtDA5E82Levf19bizO/R7QUdR2cCCK1yfed+P0/TdtKYq/69eEsWFNa1Fc3dDV6hnzGXNXh65w0HM+dYVr97v3o09f+/Upp+lpC2Go4HqHBqLoaQst67yilL+LG4rIfgDtAPYopaaz284B8KcAkkqpLyzz/FcB+D8XqgoSi8XUyMiI576zVUFstIW0oqogugiCi6gK8n7SQjBbFcSybQirgjQS35/kcnO1WSxmpcN6U0crL/o6Vxc7T0tVBbGy1QncqiDZmKsJYC+zKohpZfphVRBf+f4kLjRXWRWk+auCmJYNY+GqIBUNqB6qgtwA4IMqJ8NXSr0vIrsAvIpMZQ9faZqgp73l7IbI8s7X0bq844HMmLrbl/evKiKiepEb085pKdFoMbG3oG1nhcd6xVXG2tWtpcXAuhVILv3u089+/cppDEPD+R3hhRsu5pxVPdvSKOXxtrlSyhKRZb+drpR6HsDzyz0PEREREVE5vt9jDeAVEdleuFFEBpB5x5qIiIiIqO7VwzvWfwDgb0Xk0wBGkbn17d8DCCPzYUYiIiIiorrne2KtlHoHwC+JyNUAfgGZm8P/Xin1rL8jIyIiIiKqnO+JtUMp9RyA5/weBxERERHRUtTDPdZERERERA2PiTURERERURXUza0g9S63eHlA12BaZxcf0LTMYjBBXYMmgKWUu3iMJgJNAzQI7Ow2Li5Aq00jL/hC/nAW5rJsG7Z9diGY3EVfkikb6ezjtpCG6fmzi3RpAmia5i7yklnky0JI12ADSFs2dBGEg3rFC3PR6sQFYmrfr7NQS9qyEVh4oZa6xsS6AratcPzUNHYcHEF3WwhfvG4z9h4+hvGppLsc7n1PH8fkzDz+YmArZuYt3PnkUXf//TdtQUtAwx/89UvutgPbY9i8tp3BnIiogBNz93/vOG674kI89uKbuO2KC3HX8Nm4OzgQxUPPvoZnXpnAtZf24I5rPohdh0bz4u7Xvv8G9vzaZoQMDdu//i/obgvhD3/zEux54mhe/F5RtUIHAAAgAElEQVR7Tgs2dkUYj6nI3JyJE/FE3twaHIhiU1ekZgmnH3362a9p2nj11DR25vQ7NBDFJWvbGzK5brwR+yCeSGHHwRGMTyWx86qL3aQaAMankth7+Bh2XnUxxqeSmJhOuUm1s//OJ4/idCKdt23HwRHEEynfromIqF45Mbc/uh53DR9zv+fG0F2HRtEfXQ8A6I+ud5MBZ/+dTx5Ff3Q9dhwcwcn4rBu/naTaabf38DGcjM8yHpOneDJVNLd2HRpFPFm7+eJHn372OzEz7ybVTr87D41iYma+pv3WChPrCqRMy/2Fd4QD7s+O8akkOsIBAEBrUPfc3xrUi7alTKuGoyYiakxOzHXi7UJxt9z+3Phbql1rUGc8Jk+mrTznjGkve2HouurTz37Tlu3dr2XXtN9aYWJdgaCho7czs5b8mWTa/dnR2xnGmWQaADCbsjz3z6asom1BIz/ZJiKiszHXibcLxd1y+3Pjb6l2symL8Zg8GZp4zhmjhrcN+dGnn/0GdM27X70xU9TGHPUK64oEcWB7LHPfz/OvY9+2PncSOPfoDT3/Ono7w+hpD+L+m7bk7b//pi1YEwnkbTuwPeZ+qIaIiM5yYu7w6Bju7e9zv+fG0MGBKIZHxwAAw6NjGByIFsXd4dExHNgew4auVjd+7795S1H83tDVynhMnrrCwaK5NTgQRVe4dvPFjz797LenLYShgn6HBqLoaQvVtN9aEaVq+xZ/o4jFYmpkZKTkfs+qIErBkExVkJRpu59EZ1WQpub7L22huVqPVlNVkLfuud7vITh8navLnadnq4Io2LZyq4JYtoJeriqIUghopaqC2Ajpwqog9cX3J36hucqqICtXFcS0bBj1WxWkornKqiAV0jRBd3tj/uuJiKjRaJqgp72lbJvOSP7jc1tLt13oXESltLQYWLcCyaXfffrZr2FoOL8jvHDDBlB3/xwgIiIiImpETKyJiIiIiKqAiTURERERURUwsSYiIiIiqgIm1kREREREVcDEmoiIiIioCpqy3J6IrAdwEMDPAbABPKqUemCp58utYR00dHS0GJhMpJC2MrWr67TeIhFR3XPqVc+lLc+60oXxl2sA0ErzYw46dZ2ZZzSepkysAZgA7lRKHRGRdgCjIvI9pdQriz2RbSscPzWNHQdHMD6VxLWX9uCOaz6IXYdGMT6VdFcIumRtOyc9EdEiFMZXZyXEtee0YGNXpkh14f4D22PYvLadyTWtCK85Wus5aJo2Xj01jZ3MMxpSU/6GlFI/U0odyf48DeDHANYt5VzxRMr9gwKA/uh6N6kGgPGpJHYeGsXEzHx1Bk9EtEoUxtfxqST2Hj6Gk/FZxBMpz/07Do4gnkj5OWxaRfyYgxMz825S7fTJPKNxNGVinUtENgK4HMAPPPbdLiIjIjIyOTnpeXzKtNzJDQAd4UDeYyAz6U3LruKoifJVMleJ/LbYeVoYX4FMPG0N6kiZVsn9KdOq6rhp9al0rvoxB9OWzTyjgTV1Yi0ibQCGAfxnpdT7hfuVUo8qpWJKqVh3d7fnOYKGjt7Os8tsnkmm8x4DQG9nGIbe1E8l+aySuUrkt8XO08L4CmTi6Wwqcy9rqf1BQ6/quGn1qXSu+jEHA7rGPKOBNe1vSUQCyCTVjyul/nap5+mKBHFge8yd5MOjYxgciLqPnXufetpC1Rg2EdGqURhfnXusN3S1oisS9Nx/YHsMXZGgn8OmVcSPOdjTFsIQ84yG1ZQfXhQRAfA1AD9WSv3Zcs6laYLNa9vxrd1X5lUFeeKzvwzTsmHw07pEREvixNe/3X0F5tI2dEFRVZDC+MuqILSSvHKAWs9Bw9Bwydp25hkNqikTawBXAvg9AP8qIi9nt/2hUurvlnIyTRN0t+f/S/H8jnCJ1kREVClNE/S0t5TdXxh/iVaSH3PQMDTmGQ2qKRNrpdT3AfAtDSIiIiJaMfx/BSIiIiKiKmBiTURERERUBUysiYiIiIiqoCnvsSYi8svGu7+7qPZv3XN9jUZCREQrje9YExERERFVARNrIiIiIqIq4K0gFbJthXgihZRpIWBoMDRBMsUFC4iIliI3plYaR5dyDNFymaaNiZl5pC0bAS7WQgtgYl0B21Y4fmoaOw6OYHwq6S67e9/TxzE5M48D22PYvLadAZ6IqAJeMXWhOLqUY4iWyzRtvHpqGjsPjbrzbmggikvWtjO5Jk+cFRWIJ1JuMAeA8akk9h4+hp1XXYzxqSR2HBxBPJHyeZRERI3BK6YuFEeXcgzRck3MzLtJNZCZdzsPjWJiZt7nkVG9YmJdgZRpuX9UjvGpJDrCAffnlGn5MTQiooZTKqaWi6NLOYZoudKW7TnvTMv2aURU75hYVyBo6OjtDOdt6+0M40wy7f4cNHQ/hkZE1HBKxdRycXQpxxAtV0DXPOedoTN9Im+8x7oCXZEgDmyPed5j7dzn1xUJ+j1MohWz2FrNRLm8YupCcXQpxxAtV09bCEMD0aJ7rHvaQn4PjeqUKKX8HkNdiMViamRkpOR+VgWhLN9/0QvN1ZXAxNo/i1hQxte5upiYyqogq5rvv8CF5qpTFcS0bBisCrKaVTRX+Y51hTRN0N1e8C/UiD9jISJqdJ4xtQbHEC2XYWg4vyO8cEMi8B5rIiIiIqKqYGJNRERERFQFTKyJiIiIiKqAiTURERERURXww4tETYhVO4iIiFYey+1licgkgJPZh+cBeNfH4VSqEcbZCGMEKh/nu0qp62o9mHIK5upq0ihzqdYaYq7mzNNG/L1xzCvjPACvNlBMbcTneKlW07UClV1vRTGVibUHERlRSsX8HsdCGmGcjTBGoHHGuZrxd5TRaM9Do40X4JhXSqONudHGuxyr6VqB6l4v77EmIiIiIqoCJtZERERERFXAxNrbo34PoEKNMM5GGCPQOONczfg7ymi056HRxgtwzCul0cbcaONdjtV0rUAVr5f3WBMRERERVQHfsSYiIiIiqgIm1kREREREVcDEmoiIiIioCphYExERERFVARNrIiIiIqIqYGJNRERERFQFTKyJiIiIiKqAiTURERERURUwsSYiIiIiqgIm1kREREREVcDEmoiIiIioCphYExERERFVQV0l1iLSISKHReRVEfmxiPyyiKwRke+JyIns985sWxGRB0XkJyJyTES25pzntmz7EyJym39XRERERESrRV0l1gAeAPC0UuoSAFsA/BjA3QCeVUptAvBs9jEA/AaATdmv2wEMAoCIrAHwJQC/BODDAL7kJONERERERLVSN4m1iJwD4KMAvgYASqmUUuoMgBsBPJZt9hiAT2R/vhHAQZXxvwB0iMgHAPw6gO8ppU4rpaYAfA/AdSt4KURERES0CtVNYg3gIgCTAL4hIi+JyFdFJAJgrVLqZwCQ/d6Tbb8OwFjO8ePZbaW2l3XdddcpAPzi10JfvuNc5VeFX77iPOVXhV++41zlV4VfFTEqbbgCDABbAdyhlPqBiDyAs7d9eBGPbarM9uITiNyOzG0kuOCCCxY3WqIVxLlKjYDzlBoF5yrVSj29Yz0OYFwp9YPs48PIJNqnsrd4IPt9Iqf9+pzjewH8tMz2IkqpR5VSMaVUrLu7u2oXQlRtnKvUCDhPqVFwrlKt1E1irZT6NwBjIrI5u+kaAK8AeArAbdlttwH4dvbnpwBsz1YH+QiA97K3ivwDgGtFpDP7ocVrs9uIiIiIiGqmnm4FAYA7ADwuIkEAbwD4FDLJ/xMi8hkAbwO4Kdv27wD8JoCfAJjNtoVS6rSIfAXAD7Pt/rtS6vTKXQIRERERrUZ1lVgrpV4GEPPYdY1HWwXgD0qc5+sAvl7d0RERERERlVZXifVqYtsK8UQKKdNC0NDRFQlC07w+d0lExJhBRLXHOLN8TKx9YNsKx09NY8fBEYxPJdHbGcaB7TFsXtvOCUxERRgzztp493cX1f6te66v0UiImgvjTHXUzYcXV5N4IuVOXAAYn0pix8ERxBMpn0dGRPWIMYOIao1xpjqYWPsgZVruxHWMTyWRMi2fRkRE9Ywxg4hqjXGmOphY+yBo6OjtDOdt6+0MI2joPo2IiOoZYwYR1RrjTHUwsfZBVySIA9tj7gR27mPqigR9HhkR1SPGDCKqNcaZ6uCHF32gaYLNa9vxrd1X8pO3RLQgxoyl44cdiSrDOFMdTKx9ommC7vaQ38MgogbBmEFEtcY4s3y8FYSIiIiIqAqYWBMRERERVQETayIiIiKiKmBiTURERERUBUysiYiIiIiqgIk1EREREVEVMLEmIiIiIqqCukusReQtEflXEXlZREay29aIyPdE5ET2e2d2u4jIgyLyExE5JiJbc85zW7b9CRG5za/rISIiIqLVoe4S66yPKaUuU0rFso/vBvCsUmoTgGezjwHgNwBsyn7dDmAQyCTiAL4E4JcAfBjAl5xknIiIiIioFuo1sS50I4DHsj8/BuATOdsPqoz/BaBDRD4A4NcBfE8pdVopNQXgewCuW+lBExEREdHqUY+JtQLwjIiMisjt2W1rlVI/A4Ds957s9nUAxnKOHc9uK7WdiIiIiKgmDL8H4OFKpdRPRaQHwPdE5NUybcVjmyqzPf/gTOJ+OwBccMEFSxkr0YrgXKVGwHlKjYJzlWql7t6xVkr9NPt9AsC3kLlH+lT2Fg9kv09km48DWJ9zeC+An5bZXtjXo0qpmFIq1t3dXe1LIaoazlVqBJyn1Cg4V6lW6iqxFpGIiLQ7PwO4FsCPADwFwKnscRuAb2d/fgrA9mx1kI8AeC97q8g/ALhWRDqzH1q8NruNiIiIiKgm6u1WkLUAviUiQGZsf62UelpEfgjgCRH5DIC3AdyUbf93AH4TwE8AzAL4FAAopU6LyFcA/DDb7r8rpU6v3GUQERER0WpTV4m1UuoNAFs8tscBXOOxXQH4gxLn+jqAr1d7jEREREREXuoqsV7NbFshnkghZVoIGjq6IkFomtdnMIloNWKMIKJm1UzxjYl1HbBtheOnprHj4AjGp5Lo7QzjwPYYNq9tb9iJRUTVwxhBRM2q2eJbXX14cbWKJ1LuhAKA8akkdhwcQTyR8nlkRFQPGCOIqFk1W3xjYl0HUqblTijH+FQSKdPyaUREVE8YI4ioWTVbfGNiXQeCho7eznDett7OMIKG7tOIiKieMEYQUbNqtvjGe6zrQFckiAPbY0X3F3VFgn4Prak104clqLl1RYI4+OkP42R8Fq1BHbMpCxu6WhkjiKjhNVt8Y2JdBzRNsHltO761+0omeSuk2T4sQc1v3rTxX7/9o7z5SkTUDJopvvFWkDqhaYLu9hDWdbaiuz3E5K7Gmu3DEtTcOF+JqFk1W3xjYk2rUrN9WIKaG+crETWrZotvTKxpVSr1YQkRgW0rn0ZF5K3ZPtxDRORotvjGxJpWJecDo84fc29nGPf29+HLT/0Ix09NM7mmutIZDmBoIJo3X4cGougMB3weGRHR8jRbfOOHF2lVcj4w+sRnfxk/PZNEPJHCn/7Dcbw0dgav/Gwa39p9JbrbQ34PkwgAMJVM48FnX8N/veFSdIQDOJN9/Cef7OM8JaKG1mzxjYk1rVqaJlBKYdvQP+dtb+R7u6g5pUwLz7wygWdemcjb/qWPc54SUWNrtvjGW0FoVWu2e7uoOXGeElGzarb4xsSaVjWve625OA/VG85TImpWzRbfeCsIrWpcnIcaAecpETWrZotvdZdYi4gOYATAO0qpG0TkQgDfBLAGwBEAv6eUSolICMBBAFEAcQC/rZR6K3uO/wvAZwBYAD6vlPqHlb8SahTO4jxE9YzzlIiaVTPFt3q8FeQLAH6c8/heAPuVUpsATCGTMCP7fUop9fMA9mfbQUQuBXALgF8AcB2AR7LJOhH9/+ydeZxU1Zn3v+fW3gt0Aw0ujaKImJaA0IiIGYfojJoRZRLcIqgQZdEw+maMyywkThjzStQxGpXFKCiigpC8GjVqxi2JhigtahIUN1TahW6abui1tnveP2qhqqvuraa6bm8838+nP3Tdqlvn3Oacc5/7nOf5PYIgCIIgOEafMqyVUpXA2cAv468VcBqwMf6RB4F/jv8+M/6a+Punxz8/E3hMax3UWu8APgSm9MwVCIIgCIIgCAcrfcqwBn4OXA+Y8ddDgSatdST+uhY4PP774cBOgPj7e+OfTx7Pco4gCIIgCIIgOEKfMayVUjOAOq11TerhLB/VOd6zO6dzmwuUUluUUlvq6+sPqL+C0JPIWBX6AzJOhf6CjFXBKfqMYQ2cApyrlPqEWLLiacQ82GVKqUSSZSXwRfz3WmAkQPz9wcCe1ONZzklDa71Kaz1Zaz25oqKisFcjCAVExqrQH5BxKvQXZKwKTtFnDGut9b9prSu11qOIJR++qLWeDbwEnBf/2GXAE/Hfn4y/Jv7+i1prHT9+kVLKF1cUGQO83kOXIQiCIAiCIBykOCa3p5Q6m5gyhz9xTGv9kzy+6gbgMaXUfwNbgfvjx+8H1iqlPiTmqb4o3sbflFIbgG1ABPi+1rp/1sUUBEEQBEEQ+g2OGNZKqRVAEfBNYgof53EAXmOt9cvAy/HfPyaLqofWugM43+L8m4GbD7DbgiAIgiAIgpA3ToWCTNNaX0pMZ/q/gJNJj3sWBEEQBEEQhAGFU6Eg7fF/25RShxGrjHiUQ20JfQDT1DS0hhwtR9oTbQhCXyUSMalrCRKOmnhcBsNLfLjdfSZNRhAEIW8G0vrmlGH9lFKqDLiVWBlyTbzoizDwME3N9l3NzH9oC7WN7VSWB7jv0smMHVFaMMO3J9oQhL5KJGLy3q5mFj1ckxz/K+ZUc9yI0n578xEEQYCBt7450mOt9VKtdZPWehNwJHCc1nqJE20JvU9Dayhp8ALUNrYz/6EtNLSG+lUbgtBXqWsJJm86EBv/ix6uoa4l2Ms9EwRB6B4DbX1zxLBWShUppZYope7TWgeB4fECMILDmKamvjnI541t1DcHMc2stXEKSigSTU6IBLWN7YQihRNj6Yk2BKE35k9XCEfNrOM/EjUtzhAEQegfDLT1zalQkNVADbGkRYgVbXkceMqh9gS6Fy7Rnfhlr9tFZXkgbWJUlgfwul3dup6ebkM4uMl3/vRE7L/HZWQd/25X/9smFQRBSMXrMjijajizqkdSFvDQ1B5mU81OPP10fXOq16O11j8DwgBa63aylxoXCki+4RIJg+Lb977KKcte4tv3vsr2Xc1d9tYNLfZy36WTqSwPACQNkqHF3u5dUA+3IRzc5DN/ujt3usrwEh8r5lSnjf8Vc6oZXuIraDuCIAg9jd+rWHzaGJY+tY0LV21m6VPbWHzaGPze/mk2OuWxDimlAsSSFlFKjQb6Z7BMD9Md71e+4RJWBsWvrzqFitLcN27DUIwdUcqvrzrFMa9dT7QhDBzymUf5zJ/uzp2u4nYbHDeilA0LTyYSNXH386x5QehPiCKVs7QFTa5a92baOnrVujdZv2Aq5UW93Lk8cMqw/jHwLDBSKbUOOAWY61BbA4buKl/kGy5RiPhlw1AFNSR6qw2h/5PvPMpn/vRk7L/bbXBYWaDg3ysIgjWiSOU8Ua2zrqPRvpHicsAU3N2hlFLAe8B3iBnTjwKT49UUBRu6q3yRb7hEwqBIxcn45b6aICYMDPKdR/nMn56eO4Ig9CyiSOU8fk/2ddTv6Z87cgX3WGuttVLq/2mtq4GnC/39A5nuer/yDZdIGBSdn8jLAx7qm4MF3f6Sp3/BafKdR/nMn/KAhzXzTmTnnnaKvC7aQlFGDglQHvAU5FoEQehdRJHKeYYEvFnX0SGB/plD5VQoyGal1Ila6zcc+v4BSSGULzqHSyS8w3aGQjaDojzg4YP6lgwDeMQgH+2h/A3tnopJFQ5eelJBZl8wTGNriCVP/DU5T+64YAJDir0Mcct4FoT+zsGmSNUb8eQDbR11ys/+TeBPSqmPlFLvKKX+opR6x6G2BgyFVr7IpViQGpLR0BpiaLGXw8uLqCj10dgezmoAv71zb7fUD+TpX3CafOdRPgof7aEoP9jwdto8+cGGt2kPyXgWhIHAwaRIZZqaTxpa+evne6ltbOevn+/lk4ZWx8M1B9o66pTH+lsOfe+AptDKF3be4aHFXtuQDCsDuMjryviuzh5yu6fdg+3pX+h58p1H+eymRE2LpJscNyJRGRCE/sHBpEjV1B5i176ONM/xreeNp6zIw5Bi5zzHkTzX0b6KI4a11vrTxO9KqWLgn4GLgbOdaG+gkdBEbw9H2N2qGRYf0IWUD8tlRFgZwE3t4YzvStCV+GmreO6B+PQvFIZ8jNB8FGRCkSgVJT6WzKhKFilY8fJHtrspbkNlL9ySo6CM5BkIgtDXaA9FWf3qjrQ1cPWrO/jxOcdDsXPtDrQCWI4Y1kopL/BPxIzps4BNwAon2hpIJLZhdu3r4LqN7+y/6V4yGZ/H4NIHXi+YfFiukIxsBvCt543nZ89uz/iuBF3x+B1MT/9C9+lJIzTgdXH9WWPT5t6t540n4LXeTVEG3H7+BK59/O3kObefPwFlcz+QPANB6D8cTA/ChgGXTTuKGzbtXwOXzRqP4bB96zYUt543PmPttXNQ9GUK+udSSv2jUuoBYAdwHrAW2KO1nqe1/k0XzvcrpV5XSr2tlPqbUuq/4sePUkr9WSn1gVJqfdxwRynli7/+MP7+qJTv+rf48e1KqTMLeZ1O0dAa4tOGtuTggvhNd+0WPm1oK6h8WC6ZsFQD+NUbvsmvrprGiEF+6luCGd+VoKvx0wlvYiKee6AtTkLh6Empq4ipM+bedRvfIWK3HakV9//xY5bMqGL9gqksmVHF/X/8GLT1mJY8A0HoPxxMcnumSdKohti13rDpHUzT2XbDUZOfPbs9bR392bPbCUcdbtghCu2xfg74A/ANrfUOAKXUnQdwfhA4TWvdopTyAH9USv0W+FfgDq31Y0qpFcDlwPL4v41a62OUUhcBy4ALlVJVwEXA8cBhwP8qpY7VWvfpO1coEqXI67KMbZ44soxF00cnt2jMHKPdzjvclZCMztvpw4q1radZ4qeFQtOTRmg4YmZtKxyxnmeGgsu/cXSGx9ruWVHmiSD0Hw6mB+F8c0a6i9ftor4lyMK1Nclj/XlNLLSDvxrYTMyQ/Z1S6nKgy38ZHaMl/tIT/9HAacDG+PEHicVsA8yMvyb+/unxAjUzgce01sG4gf8hMCX/y+oZvO6YfmM2T7IGfnjmWJY+tY0LV21m6VPb2N0aypmta+Ud7uyR/vVVp+Tc2koY5IlQkoZO7R9M2dNCz9CTBVg8biNrWx6bsuGGYWT1WBs2e6fdUS2RwkqC0LMcTEWgErHOqVSWB/A4HOs80GwHpbUzi7NS6hTgu8As4C3g11rrVV04zwXUAMcA9wC3Apu11sfE3x8J/FZrPU4p9VfgLK11bfy9j4CTgJvi5zwcP35//JyNndpaACwAOOKII6o//fRTehO7GOuyIjfnr9yc4eV6cvEpRM3YU3Wxz0VbyCQcNfG4DIaX+HDbGAX59C9XrNlBoHbQKxfT18ZqT5FvfGM+43BPa5DtXzVnxPmNPaTUMiPeNDWfN7URjGgMBaYGn1txeFlRQfuX59+hx8dqT4zTUTc6W3fsk1skx76H6dNr6sEUY93Q2sGufUF27Q0mC7WMGOxjxCAfQ4v9jrWbsH0+bWhLtnvk0CJGDS3ua3/jLnXGKbk9tNavAq8qpa4G/pFYaEZOwzoernGCUqoM+DXwtWwfi/+b7SK1zfHOba1K9Gny5Mm97v4xDMWoocWUFXlYv2AqUQ1+j8GwYh9f7m3P2KKpKPHxZVMHCx+uYdrRQ5lz8pFcte7N5ORfMaea40aUFsy47mpy4oEkYB0EhnhB6GtjtafIJ9k13xtheyiajPNLhFv97Nnt3H3xRMuMeNPU7G2PsOjhmrR5d+ggXdBx3F8SHg/WcSr0P7o6Vg+mhHtFLM46VW5vxZxqx598GlpD3PLbd5lVPZIiXISiJrf89l1u/vb4PrW+dRWnVEGeBB4DntBatxKLvX7uQL5Da92klHoZmAqUKaXcWusIUAl8Ef9YLTASqFVKuYHBwJ6U4wlSz+nTGIaKecc63cg7x2VOHFnGredPoKktxJIZVRx3SCmzf/lnahvbk7HYHeEou5o7OHRw4IAXgc4Gb3nAQygS5fbzJyRlyLbubOpWrJmVAdTd6o7CwOJAH9YaWkPc8bt0A/mO323PuUjnE+dX1xLkrhfeT2vrrhfe56Zzx3FYWSDrOfkY/gdTnKcg9DXyke/sj7SHTH7zVi2r556Iy1BETc3GLZ9x6bSjHJXbM02Ta/7hWOr2xcQRvC6Da/7h2Jx5ZH0VpzzWtwMXAv9XKfU6sB54SmvdYXeSUqoCCMeN6gDwD8QSEl8ipjLyGHAZ8ET8lCfjr/8Uf/9FrbWOG/aPKKX+h1jy4hjg9QJfY4+Smmw47eihLJo+mj2tIRpaQ2yq2cnVpx9LRYmPihIfPzxzbJpczoEaq51v/GdUDefq049N88otmzWe257bTn1LMO9YMysv3NKZ45i35o0BveUmOIdpmlklo3It0kOLvTz0vSkZ25F2cX4KnbUtlblBlmR3azDruP/VVdMYXpp9u9XrdnFG1XBmVY9MGvCbanYOyDhPQRB6B49LMWvyyKRgQlsoyqzJI/G4nL3/KkOxrz2cUZimvz7MOFUg5hXglXi89GnAfOABYFCOUw8FHoyfZwAbtNZPKaW2AY8ppf4b2ArcH//8/cBapdSHxDzVF8Xb/5tSagOwDYgA3+/riiC5SGxHPbn4FL5s6kjTtF42azx3vfA+V58+hlDUzJDLOVBjtbPBO6t6ZNKoTnznDZve4dH5UwEoD3jyuqZ8qzsKgh1RnV0yasPCk3OeGwybaYv7fZdMtv28adHW+gVTLc/pCGcf9x1ha8O/PODJeLhdMac677knCILQGa2hoSWUYVU403cAACAASURBVOAO9ju7zoQiZlap08ds1tG+jGOpnnGP8yxgEXAi+9U7LNFav6O1nqi1Hq+1Hqe1/kn8+Mda6yla62O01udrrYPx4x3x18fE3/845btu1lqP1lqP1Vr/1pmr7FkMQxE1YWEWI3dW9UhGDYt517LdtMuKPMnf7/jddr7a15GhLpBQHWgLRdK+oyzgyfqdXzS18937NvNBfUteCgVW2dZ21R0FIRdaZ5eMypWovbs1yPy1nTzJa7ewuzVoeU4+8lQupbKOezunUGN7OOPhdtHDNTSmzBVBEITuELbQ8g87rEDUWzJ/TuFUjPV6YuoczxJT9nhZa90/g2V6mFzJfFZe3qHFXvweF4cO9mfVyC3xxf6rJ44s47JpR3HByj+lhYocM6yYL/d1UNccZHDAwxlVw3l+Wx0ATe1hy/LmCUP9pnPHobU+oLjofKo7CgcfB5rgmq9OtLUn2frBzmVR0txl0798qozlU25dEAThQLAycJ2W9vQYKmuom6cHQkAjEZO6lmBB1dScirFeDVzc38MveppwOMoX+zqobw4mY6d/8I9jk2EbkYiJUtlv5ENLvLSHopT4XCybNT4t5vPe2ZMo9rl49ppvUOL3EI6arJ57Ivf9/mM21NQy/6EtrLvipGTyY+IcgOe31bGpZif3zp6UpjiSiLG2MtS7EhfdOdva4zZo6YjYVncUDi7ykWEqD3hYMaf6gMMmXBZzy6Wsx7HHpVg+exJXpsyN5bMn2cYkmlpTXuxhzbwpSYm+iBnFtPGo51NuXRAE4UDwxnWsO6+BTutY+7xG1lA3n9fZdiMRk/d2NWe02101tYLqWCulTtNav6iU+k6297XWvypYYwVm8uTJesuWLT3WXmcvXJnfzaeNbezcsz9poLzYw70vfcjN3x5PecDDe7uaaQ9FiZhm2g323tmT0Frz/Ue2sn7BVB56bQcXTjmSPa0hOsJRSv1u7nnpw4wkq+WzJ2FqTUfYZPggH/+6/m227mwCYpPp0flT+aKpnab2MC9s28X8U4/GUIrP9rRx1wsfsHVnEysvqWbpU9syJmK+cdH9QH6v1zvT02O1N2lo7eD9r1oyDMpjDymx1FWt29fB/X/4iPMmH5GW2X75341m+CBrLdZde9v5eHdrRltHDytmxODsCh97WjtoDkYJp+hYe9yKUp+LIRb927W3nc/2tPGDDfurNd5xwQSOGFJk2U5dcwffufe1jHlml/BIL49Vp8ap6FgPOGRN7SPsbe+grjlMbYodUjkkwPBSD4MDzulYf9HUnnTOJagsD7Bh4cmW6kq91G6v6Fj/PfAicE6W9zTQZw1rp0k1GJVSaK15f1cLd73wAfUtQTYuOpn65mBG0sC8U44iFIlS12Ky6OEabj9/Ar9+8/M0OZxn//IlMyYcxi8vrQZg9tRRfFTfym//8iXzTz2aeWveYMmMqowkqyvXvcmaeVOYec8raV7o/TJ6ZrJUM8AHdS3cdG4Vfo+R9CpbxXTnu0V9sMgaCV2jPWST1GIh/xQxTf7x+EOZt+aN5Fz6+YUnEM2hChKMmhlz677ff8zi04+x7d/NT23L2ML88TnH2/RPJ43qxDX9YMPbtgmP+ZRbFwSh/9IbTqaOkKapNT158Y4LJjDI58bimb8ghKPZ17dI1Nn1zal2C2pYa61/HP93Xuf3lFKzCtlWfyKbbu2yWeN59PVP+eGZY7ntue2Eo9mTBtZePiUewB+LfTK15tuTDk8zGu6dPYlXtu/i1LEj+HJvRzKMZPFpMZWQ2sZ2ywTExDxNJEEumVHFwrU18ZhUIy0Gur4lSKnfQ+WQQLKAjdsixlTiooVCkF/Mn+L/rH8rbS79n/Vv5VQF8bmMjLl163nj8dlsgxoKrvrmMTS2xpIIvS6Dq755DDYVzYnkkaiTb9y4IAj9j96q9hi2eOh3Wp3DZRFj7fSDhMci9MXdzdAXZwNY0rmjB9vqU2TTa75h0ztcevIoQhGTW88fj2mhZGAoxX8/vS2ZJBXNkrV794sfMPmoYVz6wOuct+JPLH1qG5dNO4q7X/wgGTOVSECcOLKMlZdUs37B1KRnLrW9soCHyvIAa+adiM9tMMjvZsPCk/nzv53Gr686hVFDixla7Ofw8iKOGFLEIYP83Hfp5KTKgcRFC4UkMX5TyRXzl68XImKRER+xMXgNpTL2BhVg2OwYet0W12QT05dI9JV5JggDH6saDw2tIUfb7a3kRb/b4IdnjsUbX9e9rthrf4GqRlsxvMTHijnVaevqijnVDC/p3q65YyXNs9DrcVS9hZWSx6FlAS6L61E/tmBq1ienve1hnt9Wx9KZ41gxpzrrwLfSmV4yo4qWYIRls8bz4Gs7uPviibSHomkxpMvnVHNBdSUbamqpLA9weHmATYtOZndriO8sfy3n03J3yr32g3hqoZepiC98nZNLKmwWPiuljlxjy8qTbGdYa6AtFM0I4bK7DXnd2VVBvG7r/hmG4phhxaxfMJWIqXEbiuElPpkvgjAA6a1Kqx5X9rXT7XCBmKipe0U/2+02OG5EKRsWnkwkauIukCpIT3qs+6cgYR4k9KA/b2xjT2swqeSRSmV5gM8a2pIDeNlv3+OOCyakPTn9/MIT+PETf4sbBQZjhhUztMSb8V1Wcc5Di73UNQe57bntzKoeSXmRN8Mjd+XDNVw5fTRnVA1nxZxqfvKbv/FW7V4Wrq3p8tNyIi768PIiKkq7drNPbHV9+95XOWXZS3z73lfZvqs565Nx6t8zVXdbGPgYhmJoiYdH50/lleum8+j8qQwt8diOMU9czi51Lt163vic0k1W3nGvjXc8Hy93R2h/LPeL1/49q+eeyK/f/JyOkLVHPRIx2V7XwoWrNvP3t77Mhas2s72uhYjEWAuC4/T0PcjKZlA2CkWFwKUUd150QtraeedFJ9gqIxWC3tLPhphxfVhZgCOGFnNYWaDbRjUU2GOtlPoL2Q1oBYwoZFt9jYT31TRNdreGWLi2hooSH9efNZbVr+7IkMBbPnsSP3rib8nzt+5s4qfPvMf6BVMJRzU7drdy89PvUt8S5L5LJ1Pmd7O9roW7Xng/7bvOqBrOIYP9bFx0Mg2tIVa8/BFbdzZRWR6gotTHqt/HXi99ahtrL5+S1QBvaA1x/Vlfo7E1xPPb6rj8G0dn/Vx7OMrnjW0F8S5bbXV1VhPprVgzoW/Q1B7ii6YOrnnsreT//50XnYDP7WJIcXavtSYmT7d05rhkZnvA68r5ZG8oWDlnEnXNoeR5w0u92A0zM4+t04DXlTWW2046r64lmLVAjNNZ84JwsNMb9yC3Cx6YO5nPGzuSa9Hh5X7HPcfFPsWggCdt7RwU8FDsc7bdfNbRvkyhQ0FmFPj7+gWpE2/JjKqk/NySGVWsfnUHs6pHUuR1sXruiYSiJoP8HjwulVTWSFDfEsTjMgh4FceOKOHO707E7zEo93vSbqz1zSGWzKiisjyA1nDRqs1pSZEPvraDq08/lnd27uFHM47nP86uImpqdu0LZt3maWgNMbTEx0+feRewLgjzUV1Lsiz6Q9+bQonfTThi5mVod3Wrq6sGuNA/ONDwn46wmTSqIfb/f81j9omIUVNz70sfxuYdLkJRk3tf+jCm1GGDisvlpW5HLp89CTtnjVXyrl2xl4hFovKvrpxmc46ZtUCM01nzgnCw0xv3IG3C3rZwhjqH06ERzR2ajW98li5V+sZnzD3laEqcU9vLq9BWX6agoSBa60+BWuB+rfWnnX8K2VZfInXipapvHDbYz2XTjmLpU9v49r2vMW/NGzS1hVFK86Mn/sqyWZnb1VHT5Ny7Y+ERF9+3mY5wlF0twbT4z607m5KhGtliq6878zjueuF9hpQEaGwLMfuXf8brjkn8dQ7UXzZrPJtqduJz75fQW/HyR1n7dtcLHwCxuNdd+2K6unZhHHbbZ1blzDurHPRWrJlQeA4k/CdBPomISpGcdxeu2pxM5s21mxmO6mShl0Q7V657k3DUun9Kwe3np4dw3X7+BNu2OizGdIdNWIfPbXD9WWPTrun6s8biczi5RxAOdnrjHmSlzuF0aIRGc+rYEcxb8wan3f4K89a8waljR+B0JK/LUBmhsHdcMKHfGtYFT17UWkeVUm1KqcFa672F/v6+SOrES/X2+j2ujBv1DZve4dH5U7n8G0djas0t3/k6fo+LwQEP1298h9vOn0BFiY/axnYqSnzsbQtz5bo3kx7q1AluFVvdEozw/LY6tn3ZzOq5J1JR4mNPa5jrNr5DRYmPpTPHMWpYEQ0tIVb9/iP+5bQx+D0qKa23dWcTD762g0euOCk5sBc/sjVZPGbR9NEZHrfOT/C5ts+ylTPPpnIgMmMDh92twayeH7siJ/kkImoNv9++K02PeuOWzxg19Cjb/lllxNvJ4Jka7v/jx2me5Pv/+LGtd9xtGFmlpey83NnUgK7b+A4bHJbBEoSDHY/bohqhgw+1vaXOoTU8+NqOtPXswdd25Nzt6y4KGFbq5dH5UzG1xlCKiBntt4oXTqmCdAB/UUr9DmhNHNRaX+1Qe71KqvGX8PbesOkdWoKRrJNjT2uIC1dtTnqMb376XW781nHUtwT5bE9bUtt60fTRXLnuTSpKfBR7XTz4vSl81tCWLCozfJAv64QfUuzlN4tP4Yu9HURNk0XTRyfLkdc2tifDOdZdcRLzTjmKX7z4ATedO85S3aO+OZgWtmKliZ36BJ9r+6yraiJdNcCFvk9H2MJTG7b21CYSETsraNglIpb4DGacUJkWw7x8TjUlPvsbYT5hHUrB5d84OllIqSsea69Lsfi0Mck5mdCi99rET0Ys5Dgj/TMEURD6DV6X4t7Zkw5ovna/zd4pLW7Ed/tS88GWzRpvm2dSCHweRV2LyZUPp6/Z5UX907R2yrB+Ov4D+/cQ+udfqAukGn8Jb+9jC6YSjppZJ0eR18XEkWVs3dnEDZveYenMcbSFotxz8SQMBbtbQtwzeyJRk3jZcfj+IzED++rTx/A/F07A5zKIaM3y2ZOSXvHETf3mp2OV4JY+tY17Lp7EYYP9WW/K9c1B9nXEvNs/PkdnrXpomhqXASvnVLMwHnbSForm9CJ3ZfusK1UWuyPnJ/QtXMoiji7Hf+WQYg9r5k1JlgyPmvZbsC1Bkys7hUhd+XAN6xdMZXCR9Xl+r5FV2s/vtb6ZuZTC7zHSkn38HsM2i74jYiZv0on+XbXuTdsiDH5P9p0bv0dCQQTBSVqDUe5+8YM0L+7dL37Aj885njKb9aQ7KAV3XDAhGQ6SCI1wWJwDs5c81q02a7ZTf2MnKbQqyEygUmt9T/z160AFMeP6hkK21ZdINf46wlHCUTNWDnzD2xlqIMtmjefW595LeqW37mxi1LBifG7FTU/+jee31XFG1XCuO+s4GlpCHDLIj0bzi++eQMDr4sumIHX7grSFohxW5su4qfs8BvXNoaRX+fuPxMqWWyUtJgrCeNxGRmJZecDDB/Ut3PG77Vx68ijWzJuC321Q7N9fkTFh7B81rBiNxjRjBnohQzikzPnAIOB1ZfU+26lhmFrT1Bbh2sdr0h4eBwWsk3iiWmdN9DO1vXs3HNEYBmnzyTBix+3auqdTouQ9L33ITeda34jy2eYdVuzj0fknEYzo5AOGz60YZqGMIghCYYhqzfPb6nh+W13a8f+c4ZyxGYyY/PSZ99LWsJ8+8x4/v+gEx9oEMAz41zOOxW24MBQMLfHxr2cca1tJthBEzOxrtp1saV+m0B7r64GLUl57gWqgBFgNPG51olJqJPAQcAhgAqu01ncqpYYA64FRwCfABVrrRhUTdLwT+CegDZirtX4z/l2XAf8Z/+r/1lo/WKgLtCJh/NU1d/Dd+zZzy3e+Tn1LTEP6oe9NQevYNstX+zqobw5xw6Z3uOU7Xyccjd0ot3/VQn1ziIkjy/iPs6uo29fBDx9Pf1o1lErLEr539iTufvH9tAlfWR5g6cxxhOPJXbWNsbLlnbeyEuoh351yJHdcMAG3ATvjSYaJkujXnH4sPo/B9785hu8/sv/clZdUM3Z4KU8uPoUvmzqSnuzUOGoJ4RA6UxbwMmKQP81wHTHIT1nAekyYmmSYBcTG87WPv816G++uzxVL9MsowJJjGzWqNQseqsl4GNyw0D6OOdvWqZ1jyW1RvtcuUcc0NXvbIxne9EMHadm9EQQH6Y3dIo8rJiawcG1NWptOh4J4DINQRHPFutfT7AyPw5a1321w07lV7GkNA7FQmJvOrXK88qJTFNqw9mqtd6a8/qPWeg+wRylVnOPcCHCt1vpNpVQpUBOP0Z4LvKC1vkUpdSNwIzHv97eAMfGfk4DlwElxQ/zHwGRinvIapdSTWuvGwl2mNeFITMXg9uff5/bzJ3D/Hz+mNRhJC9dYNms8tz23ncPKAlz6wP4BfP9lk2nuiGDq7BnBS2eOy9g+XjKjKs2wrm1s58ihRbgMxW8Wn0KJ341SisEBD48vOpk9rSFqG9t58LUd/MtpY4iYJgGvi9rGjgzD+84X3ue6M49LGtWJ71+4toZfX3UKQNKoTryXGkctIRxCKoahOKK8CL/HRThq4olXubIbE1bVEO0SCq2KttgZ4xBTBcmuQGJTeVGTNKoTn79hk31bPrfBdWeOpbaxA4jdRK47017ho64lyF0vvJ/m0bnrhfe56dxxomMtCA4yrNiX1Unk5G6Rz60ywjyXz56Ez6Y6ayEIWoSp5Vo7u4tS4PcYjBxSlBby53Toi1MU2rAuT32htV6c8rLC7kSt9ZfAl/Hfm5VS7wKHAzOB6fGPPQi8TMywngk8pLXWwGalVJlS6tD4Z38XN+iJG+dnAY9258K6SiIEYuvOJm757Xv87LzxySQq2H/jXTpzHPvaw2k3yn3tEe77w0f8+9lVWW/wRZ22zGsb2zM8wJXlAb5oaqei1EdbKJo2MW89bzwVpbGEx1nVI/nRE39j0fTReF1G0hOe2se135uCx20w7eihbKipTWu3PRQBhW0ctYRwCKmYpuaD+pYDKrTgsfDu2upE52GMQ34KJPkqiezOVr7XxnMPOqtn/CAqaCsIvYJhKMZUlLBh4clddgh0l2DY5Bed4rp/8eIH3ORwrLPV2ul0SIZSilAUrnxwv6Nx+ZxqxytNOkWh/ex/VkrN73xQKbUQeL2rX6KUGgVMBP4MjIgb3Qnje3j8Y4cDqd7x2vgxq+M9QiIE4oyq4SyaPhq3S1Hb2M4F1ZX87genJksYjzu8lIpSH4cM8jOs1MfXDi3l0DI//zVzHIYiq8ZzWyiacSy1xHniZvvQnz6hyOvO2EK/buM77NzTziC/J7ktPrTYS5HXlTaZJo4sY8mMKjTwwa4Wrjj1KC6orkxr992vmvmorrVLWtSCANZKMQ2tIctzAl6D/5hRxeiKEipKfYyuKOE/ZlQRsEko9LiylwPOVbXMa1EK3WtzA00Y453bsgvrCEfN7OV7bbS5rTzjOcLGBUHoJgmHwAUr/8Tf3/oyF6z8Ex/UtzgqfRc2NfXN6etifXPIcQPXbbGe2TkyCkE4kj15MWyj7d+XKbTH+gfA/1NKXQy8GT9WDfiAf+7KFyilSoBNwP/RWu+zeWLJ9oa2OZ6trQXAAoAjjjiiK93LSeLp9pp/OJaFa2tYd8VJPP0v38CEDPmvX7wQi49OjXmed8pRHDLYn6FOcMcFEygr9iY9aokkruUvfcTSmeM4YkgRH9a38OBrO7hs2lHJkI9UEl7vL5raWfLEX1k+exIVpT7e/bI5+b0TR5bxwzPHpnnGbj1vPItPP4YNNbVpoSxARjKaxFE7gxNjtafJp9CCGa9A1lnqqsRj/fAW8Bgsn1OdXKgT8y2QKyZSKYo6lUIv8rqw24/0uY2sUlx2YR35eNRNC7m9vpbbMxDGqXBw0NWxmo/+fnfxuw3+/Z+Oy1AFcbogVFkg+9pZFnC23d7ylDtFQQ1rrXUdME0pdRqQ2LN4Wmv9YlfOV0p5iBnV67TWv4of3qWUOlRr/WU81CMRUFwLjEw5vRL4In58eqfjL1v0dxWwCmDy5MkF+x9sbA+zcG0NFSU+9nVECHhczF39esbTWCI+OuF9uvW88XSETaImDA64WXfFSShiXrFE3NH6BVOpaw7SGozFYs+qrqSpPYzHrSgLeJhVPTKpgZ1tW7stFCUUr2Z35bo3uXf2JCqHBJIG8qLpozM8Y9dtfIfHFkzl99dN592vmpNqJgA/e3Z7Mv5K4qidw6mx2pPkoxTTETEtpa6saAuZ1OzYzSPzp6K1RinFi9u+ZMjxh1Juk+nRHo6ybvNnzD/16GRhmft+/zGLTzvmgPv3I9sCMQdevtdnkUDl62NyewNhnAoHB10dqx3haFbFCjv9/e5iarLmWT2+8GTH2gRoajcp9sTsjIipcRuKYDgcOy4lzbuMIzrWcUO6S8Z0grjKx/3Au1rr/0l560ngMuCW+L9PpBxfrJR6jFjy4t648f0c8FOlVCLe+wzg3/K+mC6SKlUXjXuXlsyo4sqHa1h7+ZSsE7MsRTJs2tFDOawsQH1zkI/qW9hUs5P5f3c0HrfB4ke2pnmPhxR7CEWMtKIUK+ZUc3iZn6ElXq4941j+8H5dhictIW32X09uAxKx0lEGB9yMGlbMYwum2kqBBbxulj61Le39+pYgXrdLYqmFnAwt9vLQ96bwaUNb0iN85NAi2x0OpeCqbx5DY0q2+FXfPMY2qcXjUkwbU8FHdS3JdqaNqcCTIxTE5zb49qTD03aWbj1vPF4bL5FpWklxVVmekyjf29kbZXcT6Y0EqoOVUTc+nftDKXxyy9kO9UToC/hc2RUrfA4WiAnHnV+p1Da224aLFYISn0Fb2OD9XfvXzsohgZzFtbqLUmSVJu6ndrVjBWLy4RTgEmIVG9+KH/t3Ygb1BqXU5cBnwPnx954hJrX3ITG5vXkAWus9SqmlwBvxz/0kkcjoFJ3Ldz+5+BRWzz2RI4cWsWRGFQGPK6v8V0JXd+LIMuacfCSzf/nntEF13x8+5rtTjszwHq+ZNyWp65s4vujhGpbOHJesqrhiTjWHDPKx7oqTgNjN/MumDv7ryW1Jb3NleQANdIRN6vaFGFbixW1R8cntMkRCT+gWpqkztKRNvV/7PBsupWgPRTMS/ewKsGgNDdmSA/3W2texvpC9bLiNl8iyWqNN/9yGomKQL63ojduFbRyjFEoShN5BKUVbljXIycQ6I49E6kLQEdbsbg5mXOsgn5vBDrbbW6XUnaLPGNZa6z9iXZ3x9Cyf18D3Lb7rAeCBwvXOnkRSVkWJL3nTTx2Yj86fmvWGfdv5EwC4+vT95Y0njixj0fTRcUmu4+gIp8ef1jbGdKntVEMShvYjV5zEvvZwsiz69WeNTZYmrywPcN8lkzlksJeWYJRQxOSSB15PXkPqQ8CdF52A32PIzV1IEomY1LUE07Lk3Tni//a0hajPtmj7PQwflH2fMWwhnWdXpTCfcwAiUTN7kQI7L5GFp8XunmtqTUNLiGseeyttjhWVS9KvIPQ1QhbJxrnWk+7gt8jdcFrXOWxqVr+abuCufnWHbWhbIfC5Df7ltDFZ5AX7VqhbV+kzhnV/JhSJxWD98MyxdIRNrtuY7k3eta8jqyF86GA/L1779xhKWSYO3jt7UrL8OcQMYlOT9Wm2qT2c9v0akkb1oumjKfG5k16yTxvaKPG7+GJvrJJjwtipbWznZ89uZ+nMcRw1rJiv9nVQXuRNFvEQCT0hEjF5b1dzRrGS40aU2hrX+dyg8pGzy6eyIcQW92w7S3aLu1UJYLsbUTiqk0Z1om/XPPaWrVZs512xrkgVCoLQffJZg7pLMGLy5icNPDJ/KqbWGPE8kaHHH+pYmxArYpdN1tPBqBcgdr3Z5AX7q8e6fz4O9DG8bhdXnz6GGza9kyFdBzGPdjYJm6ipk2U7Ny46mZ+dF1MGSb3hXrXuTa4+fUzynFvPG0/UjLJ8TnWaLNi9sydx2GA/Ky+pZuLIsmTg/4XVlfzwzLEsfWob59z9KnNXv05rMMJdL3zAh3WtLFxbk9HnrTubmLfmDXa3BCn1uzmivEhu3kKSupZg0qiG/TskdfHdECvyMXi98dCkVCrLA7ZVFH1ugzOqhrPykmrWL5jKykuqOaNquG2sNFgXlrHLTPfHPS1Ln9rGhas2s/SpbfzLaWNsPUv53KjzkSoUBKH7eCzWICerIHpcikmjhnLxfZuZfuvLXHzfZiaNGpozT6TbpDgK1i+YypIZVTz42g7HZT0j8VyVhWtruHDVZhaureH5bXWOPrwkME1NfXOQz+OVpwshoyge6wIwtNjLUcOKqW1sp6k9nCZdd/1ZYxk5JMDKOdVppb+XzRrP+tc/ZfbUI5OKIYnj9c2hpIe6trGdoyuKk55tpWBfe5iOsMnDl09BE1MMufnpbdQ3h7j69DHcdsEE3IZi7Ws7OOeESu564f10RZJ4xcaEQZ3a5wSV5QEaWkMsXb8tWUlREMA6scY2ZIL9RnLncWZ3gzIUWRP97J7z3IbKuq2YS4s1Lxk8YlrbqfHSYGL3l8gnAz4fqUJBELqPy2INctLGDUd171RANLJ7rJXDLlif22Dh343ivMlHJBWZNm75LKczpLs4tRMoHusCYBiKIl9MDmvFyx+xbNZ4zqgazo/PjSkD/OQ32xgUcHPLd77O//7rqaz9Xuwm/HfHDs8oF37DppjkXYLK8gCmqbl2w9t83tTO7F/+mXPufpUfbHiLlmAUj0sx+5d/pr45xA/PHMuSJ/7K6be/wuxf/plTx47grhfeZ1b1yLT+1ja2UxbwxDJ+U/rcudDMipc/kpu3kIGVB8edw4OTMJJTx1kuIzkYNXl8Sy2r556YLK70+JZagjZGfEfETBrVsP9hsiNHsQGr4gh2Bq+OF3KYu/p1Trv9Feaufp365hDaxhhPZMB3nm92f4eEVGHnvkkxJkFwrjUY1gAAIABJREFUlmDU5KfPvJfmxf3pM+/ZrkHdJWpqKkp8abtuFSU+xz24ppm9EJXpcJ2WgFdxzgmVzFvzBqfd/grz1rzBOSdUEvA666F3aidQPNYFwIzrPSa80rc9t51bz5/Azj1tLHniryyZUcVXe4O4DMXc1fulvNZePiWrFyqhslFZHuCeiyfx1b4O/v2fvkZLMMLy2ZPwe1y0BCPUNwcJxL3OS2ZUZZ0QS2ZUZS17npA6u++Sycxfu4XbnovFVR85tIgvmtqTWtVy8xY6U+Q1WD57UoZHuMimGiLEDN7EDSoRR/fTZ97jzotOsDzH5zI4f3JlmgTeHRdMwGdjxJvdiLHOdl12Mdb5JErmkwEvijyC0Dv4PS7qW4IsXFuTPFZZHsBvU6Squ+ST71EILMPUHI4Fae0ws4YXblgwlcGBHCd3A6d2AsWw7iaJrYQ7fredG7/1NR6dP5VQ3DOWCLUYXuqjNRjhxl/9JW3gRM3sSYiHDPazfsFUmtrDuF2KX7/5OZdOG8V9f/iIy6YdlXbjX3fFSVSWBygLeCyN9CGdKjaunFPNIWU+ygOx8I5fXTWNjrCJW0FbOJrsp9y8hWwEwyYet0oLf4iYUYI5CiZ4XCrrDcqu1HhU66yFEjYstDZc8y02EI7qrAk0/3XuOOv+5RE+4nUbzP+7ozO2lu22PUWRRxB6hzKfO3s1Qp9z5pNVvofToSCWa6eD0oIQc1BkDS902EOfT9GyriCGdTdpag9hmpprTj+WSx/YHyu9YeFUhpb4qCwPUOJzZ70Bt4ciGVJd91w8Ca9Lcctv36O+JcjquSdy5fTRXPLA61m90jc/vY17Z0+ioSWUdYBUlPp4ZPMnSc/18FIfhw0OpKk3pJZljURMNiw8mUjUxB2XUZObt5BKVMMVD9ZkjDU7vWcAt8peGMVO8zkctVhwo7lDLQ602EAoalLfnL4FWN8csi3K4Mkjbtw0NV63kVY63es2cnrURZFHEHqe3W1hfvHC++kP3C+8z03njuMwrzMmVD75HoXAUHD7+RPSis/dfr59uF4hsDLonbY9nNoJFMO6G5imZk9riIDXlTSqIVZFsaElxC9e/IBls8YTipppXuMEu1tCbP6onoe+N4U9rSEaWkPc89IHLD5tDP/9z8cTNjXXb3yHG791XDIuuvNke35bHT+aUUUwbGZsY6+cU80hJT6uOPWYLnm5TFPzQX2LSHoJtmidfdHXObYLI1ozrNTLo/OnEtUal1JEzCgRm/PyWXANpbKGWvxkprXnGay3X+08yW4je2KT3Y5tMGpy05PbWDR9NEW4CMVf3/ndibb9EwSh54lEzezVVc92LvDYqvCU0yW+XYaB35P+0O/3GLgMZ0NQPIbKqJ9x63nj8Th8vU7tBIph3Q0aWkPs3NNOqd+dnACJAi+3/PZdZlWPZFDAw+CAh3DUZMWc6jTt35FDAhxdMSpZcTHBti+bWTpzHAGvi607m5KqHVbqHR0Rzfkr/8TEkWVpxsSQEi8+n5uKLm5ZWQXyiyqIkEq+22del0E4ahKMmBgqZmh7XMpWOs9jUf7bbsFVwLxTjspYpHMtlabF9usGm+3X9nD2uPGf28SNW8dsSi65IPQ1XIbKqljhpJHrNhSrLq1m195g0sAdMdiXU9mou0SiJt9/ZGvmbqTDISim1gS8rjSDPuB1ZVTq7S+IYd1FTFPT0BpKe6oJRaKUFXmoaw4mDY1F00fTHo5mSNbcfv4EyorcaQMnGI7icRlZvX9FXhfDB/mSqh23njee1a/uyNjiXj57Ei4jNvi37mxK3qwrywP86qppB3SNIukldIWhxV4e+t4UPm1oS47lI4cWdWn7bG97JKOaWLHNdqpSMLjIkzZvBhd5bCsbdkRMfvbs9jRj92fPbrc1diEWz32giTseI3vcuJ3hP6zYl3X7cVixPLwKQl/D7zGYcUJ6AvXyOdWOPgh73ArTJK1K7Yo51XjcvRPrHHY4BEVruPelD5lVPTK5i3fvSx9yk8MFYpyS2xPDugt0/uOfUTWc/zy7ChQMK/Gx/OUPk97o4aU+Ah4XCzelZ7he+/jb3Hb+BPweg+GlPqJas7slxJB4HHbnJ8S2UBQ03HreeAylMJTix+ccj6k1jy2IJUh6XAb7OsJ8tbcjw6uXz43aqUB+YeARjJhpi/59l07u0jkHqs0ajmpue2572oJ723PbbRU03BbGbi5vj8vIHi9ttw3q9xoZO1Er5lTjt1FIkUREQeg/dITNZOIixOU7H65xNJGwPWRyV6e47rteeD+27hU71qxlCIrTnnKPRUlzj8MqKE7t0oth3QVS//gTR5Zx2bSjuDgevnFG1XCuO/M4Sv0uVs89kUF+N23h7J7fw8v8fLW3g0tSkhxXzqlm9dzJ3Bo3HhIqHlHT5P/Gw0kSBsL6BVO5cNVmKssDrJ57Itdu2Mqi6aMZWuxlZNxDHY6Yed+oRdJL6AoNrSHu+F26R/iO323n5m+Pt12MrBJy7DK/rUrs2g3tEp/B6nknUrunPenlrhwSoMSXW2f7nosnsqc1nDxvSLHHXmc7rPnNWzGd7dRt4rmnHG3fliQiCkK/IBLXlE5d7xIVk51CWax7DotzUOQ1WDPvRHamrJ0jhwRySql2F9PUlBd7eGzBVKKmjofZ6IJUQbRD5PZ6kdQ//qLpo9OUOZ7fVse//uOx1DVHuTte217r7DJ64WimdNjCh2tYM/dErjn92LTKjLefP4H65hBlAU/y/Kb2cPI8l6HYurOJpU9tY9ms8UC6ukc+iCdN6AqmaXL5N47OyBw3c1QRyMcbYursBQvsvEXBsKapNZTmUb/jggkMzpFrYGpNRzjdE3/7+RNskzJDUZOVf/iElX/4JO347KmjbNsSBKF/4LdIavY76E3Veax7hSBqxvJGUtfA5XOqcbAWDgBet6KuKZIhaVhZ5qzzwaldesmW6QKpVc8SyhwTR5bx6PyTePmH0xkU8FDkdXPDt76GqWH9659mVFZbMacaDVmfjjxuI2lUJ45d+/jbXH36mGTC4vLZk1jx8kfJ73O7jGQVqAdf24FRoKzdhCft8PIiKkpFak/IxNQkjWrYP15zORe88QIsqfNi+exJtqobpkXcs11SS8jMrn0dytFBncd1JVRLUukJmShBEHoGDax+dUda5cXVr+7ASV+qVb6H08l8wUj2sJdgjqq13aUtlL3dtpCz7SZ26VPvSSK310OkhkiYWvP4wpMpK3KzuyXET5/ZlnXL5omtn3PLd77OYWUBPm1oo7kjTLEv+9ORlfEwalgRLR0Rls4cR0fYTFZCXD6nmnV/2sHKP3wi4RpCjxOOmhYJLvaLoNaa0oA7rbCM24WtRzifuGeroi25thXzKfbitlAtcTomURCEnkFrnfUen0tetDu4lIXMqMOxIPmE6/Xndp3apRePdRdI/PGfXHwKgwKe+NNkB9dtfIdZ1SOzbtmcXjWC1lCUW377LqGoSYnPTanPzco51WlPR8tmjeervR1ZvV6fN7Zz5bo3YxrYQwK8ct10HvzeFAIeg0tOPorfXz+dX101TXSmhR7FsPLS5lj0w1HNnF++zj/8zyucdvsr/MP/vMKcX75O2KbYi6FiOtGpc+aOC+wLFngs+pfL2LW8LpvzPC6VVC1Zv2AqS2eOY3CRB49NNUlBEPoPVuFoTtp8Kl6oJXXd64lCLe48187+2i44s0vfpzzWSqkHgBlAndZ6XPzYEGA9MAr4BLhAa92olFLAncA/AW3AXK31m/FzLgP+M/61/621frC7fTMMRdSEO//3fW741tfY3RzEqmhLbWM7hwzypyVeTTt6KJecfGSyZPLQYi8VpT6e3Po5f/liL/dcPInvP7I/I3bFnGqUgnVXnERrKEJ7KCbt1x6S2Gehd/G7jawlfnPFHOaTBKS1xtOpSqHHbdh6i9wulVEsafnsSbal0yG/IgVRE763ZkuGZ+lXVx6Y1KUgCH2T3qiCaCiVtVCLcthj7fdarO0OJy8OL/FlVVcaXtI/E7z7lGENrAHuBh5KOXYj8ILW+hal1I3x1zcA3wLGxH9OApYDJ8UN8R8Dk4mFR9UopZ7UWjd2p2OmqQlFolx/1nFoDQFvTAVkeGl2ubyyIg8uQyVv7vNPPTqpg5mo4FRZHmDNvClMGjWEZ975nNVzT2RPa4i2UJT2UJQin4uAx0Wp301ZIG5IOyi1IwhdQRNLYExd9E3TzBlz6Hcb3HRuFXtaY0m4XlfstZ1BbmpYnKVgQS6JvsQDbLIEcTyx2A63WzGs1Jd2XcNKfbhttGMtw2KczvYRBKFH6I0qiKape6VQS0fIzFq+3WmZP5fLoMiTXiCmyOPCZVM8rC/TpwxrrfXvlVKjOh2eCUyP//4g8DIxw3om8JCOua42K6XKlFKHxj/7O631HgCl1O+As4BH8+1XNh3rq08/liVP/JWKEl+Gl2vZrPHc/PQ2bjr3+OQAtSoE43bFyi8vPm0M1298h/qWICvmVDOsxMuwYh9uh3UcBeFACUayV+d6LMeirxS0haJpGee3nmcvIZVP3HNUa8oCXo4eVozLUAwp9lIW8NoWegEIRTSvvl/HaVWHorVGKcWL277kzK8fZnmOaL93n1E3Pt3bXRAES3xug3tnT8oobOVz8N6cT7GqQhAxtUX59ipH221oDXHp6tcz1tH+WvW5TxnWFozQWn8JoLX+Uik1PH78cGBnyudq48esjudNZxHxWdUjk1sWtY3t/OzZ7SydOY6RQwJ8VN/Kbc9tB6CxNczSp7ZRUeLjru9OzC41phQ/Oud4GlqC3Pit4zisLMAL277kzHGHiVEtHDDZKoQWOmTIzDM5MBTNXjLcziB35eEtKvK4uOLUo6ht3K/FesWpR1HksTd2XUox9tDBXHzf5jTD32Vj+Yv2uyAMbFpDUV55r45H5k9NPnA/8WYt5048nGEOtWmVvGi3FhUCj8V663Ss80Cr+twfDGsrsv1Pa5vjmV+g1AJgAcARRxxh2VDn//Thpb6011t3NjFvzRusXzA1Wcxl9dwTWfhwDRUlPn545lge/tOOjKfe5XOqCXgN6puDzLznNSrLA/z8whO46an3OO1rh+T+CwgHDV0Zq06VZ+2M21CcUTWcWdUjk9uFm2p25lx8oxYx1nYGeYk/e8xfid9eFaShJZThGR/s99j2LxzNXgr97osnWp4j2u/pdHVNFYTepqtj1e82OHVsBR/VtSQf1E8dW+GojrXHwkvudCVCt6G486ITuOaxt5Lt3nnRCT1SeTGbQe/09YIzzqj+YFjvUkodGvdWHwok9ihqgZEpn6sEvogfn97p+MvZvlhrvQpYBTB58mTLu3vqdu/EkWUMDnisy5DHfz9qWDG1je0smVGVzChubIskK7S5XQbr/rSDc06o5KHXPkkJIXk3qVMtCAm6MlbzLc96oAuLx22w+LQxB7zoWxVasNtSbekw+aR+X1pFrq2fNjCkaCiDA9nPCZsH7hlPXFe2Uui5rkuqKO6nq2uqIPQ2XR2rVgmDTiYSBiMmd3fKE7n7xQ/4UY48kW5jQKnfnRbrXOp3O64f57ZIHHfaoHfKGdUfDOsngcuAW+L/PpFyfLFS6jFiyYt748b3c8BPlVLl8c+dAfxbdzqQut177RnHcstv32XZrPFpupbLZ0+iJRhh46KTGTHIj1LxJMYU1ZANNbVsqKkFYuXJV/7hE57+6y4enT+VBX8/musefzsZY91fs2GF3iOf7bR8FpZgxEwa1Yk2rlr3Zk7DNWph8Nol5HhcilHDSrlo1ea0uWYnZ5evjrVoUguC0BlTayKmTtsBu/OiExwt1hLtpVjncERnVTlyuuJjeyhqvVvoYNJkvs6oXPQpw1op9Sgxb/MwpVQtMXWPW4ANSqnLgc+A8+Mff4aY1N6HxOT25gForfcopZYCb8Q/95NEImN3GDHIx6ZFJ9MWjvL8tjrqm0Npg2BoiZdgxKShNUTE1BxW5mfZrPG0haJZvdup5cmDkShelxHbcnEZDC+RpEXhwMknkS6fhSXfGOt8igCEozqprJP4/JXr3rRd6PPN4g9HzKzSfmGHq44JgtB3MbVOhkZAbA265rG32LDQOWOzt2Kde6tQi9ftyrpb6HQSuFOx3X3KetNaf1drfajW2qO1rtRa36+1btBan661HhP/d0/8s1pr/X2t9Wit9de11ltSvucBrfUx8Z/V3elTwqN37t2v8kFdC7v2BaksD7B1ZxML19Zw4arNLH1qG9u/auG8FX9i4doaFBCNah58bQd+T2YZ52WzxqeVJ9/dEsLvdXHE0GIOKwuIUS3kRT7lWfNZWPIV87cq/21n8Oaz0Cc8z52LyuSMAY9L+81b8wYXrtrMvDVvsPiRrdjUrxEEYYATjlqsQQ4uDFYFYhzOXey1Qi1OlRbPRcIZlUohDPo+5bHui6R69I4YWsSe1lBGLNDy2ZP40RN/S57T1B7GUIp5pxzFdRvfoaIkpo07algRhlLc/PS2ZHnyOy86gfJATFpPELpDPol0ecnFKTJCoZbNspfNAwhYFB8I2BQfsPI+2y30yiBZDTHheR5c5EHleF7VFhJXTpYuFgShb9MrOtYa7v/jx2m74vf/8eOcWvzdpbcKxPRWErhTqk5iWOcg1aOnUCx+ZGuaskFbKMqggIf6liATR5axaPpohpf6KC/yEoxE0m7u4aiJAq4/62v859lVuAyF32tQHihMGU1BONBEunwWFlPDg6/tSFv0H3xtR87Emo6QyVNv1SYTeKOmZuOWz7hs2lGWcXR+j8EDcyfzeWNHch4dXu7H77EpKmPCpi07OW/yEWntzPvG0bb9E01qQRA64zYU91w8kT2t4eQaNKTY46gX1+NSzP+7ozPyPexySwpBe8ikZsfuNGnBF7d9SfnxhzpenK43ksCdMujFsM5B6s02FK+yVtvYnhYL9PTV3+DuiyfSHoqmebJXzqlm7CElhKOaL/d2cMPGv1DfEkx6qSvLi8SgFnqVvLzcLiO5G5Oawe3NoWQTNjUr//AJK//wSdrx2VNHWZ4TNTWhSHri0Io51bYFYtyG4tyJlclKp5XlAVZeUp3zRiia1IIgdMbUmo6wmbYG3X7+BHLXms0fraG4kzpHsd+N05tnXreRVcvfO4DDU50w6MWwzkHqzfbLpvasHi2f20WJz83iR/6cluCw8OEalsyoYsXLH7Fo+mhuv2ACPreB32NQXiReaqFvcKALy5AiL/s6lf6uKPUxpMjeAM1nSzUc1cliTBCbV4serrFNXhzs99AajrJm3hQMFfOwe9wqp461aFILgtAZU8O1j7+dtgZd+/jbjiplRLUm1ClpOhQxHVUiARgSsFjbA+JcOBAG7mNIgTAMxZiKEjYsPJmjK4pZOac6LcB+5SXVaG1S3xzMGp9ZFvCwdWcTS5/ahstQjCj1M7TELzdroc9gmpr65iCfN7ZR3xzMLUvnNhg1pJixh5Ry6GA/Yw8pZdSQ4pxJt9540YPU+XPv7Em23pB8Svt6PC4OK/UT8Bi4DEXAY3BYqR9PjsqLsP8h4/DyIipK5eFXEA52rNYgJ41cU8O9L31IKBozrkNRk3tf+tDxROp813YhHfFY58A0NR/UtyS3h8+oGs6jKfFHbpdizR8/5rzJR1jK6iUM8MMHi+KH0LcwTc0nDa182tCW9FAcObSIUUOLbY1Kt9vgsDKLCi02bfncKs2THDWjtoa828hekctt2M8jj8fF4eVFB9Q/QRCEzliVFzcclOjwGtljrL098KCfz9oupCOGdQ466/zWN4eobWxLVwWZU83GLZ9lKCWsnFPNkBIvv7pqGsOKxfsl9D2a2kPs2teRUf67rMjDkAIr1QR8in1Bg5179hvxlUMCBHzW82J4iY8Vc6qT4SCJGGspoCT0FUbd+HSXP/vJLWc72BPBCYYVebMqZQzLEfrWHVwulVXZyOVw8qJQGMSwzkFnnd9F00dnVI+7Mh7zqVSsomJUa/xuF8NKxJgW+japCbewvxri+gVTC54FHgwrmtuCHDuihIipcRuKXXvbKAt4wZ/9HLfb4LgRpWxYeDKRqCkFlARB6FF8PjfHDitm/YKpyXVrWJEXn88586k9bGatgJiruq3QNxDDOgedJbhSS5QnqG1s58u9HRT73N2uMS8I3cE0NQ2toS4n31nHMBe+b0OLvexu8XJhSnnyrqhuyNakIAi9icfjisluxtfVruRrdAezF+K6hcIhhnUOOktwWZUoP6wswCGDJClR6D0SVUI7y8XZPez5Pdm1m+10ovNFVDcEQehv5LOudhfrdVk09fsDsp+aA8NQjBgUk59Zv2Aqfo+RUWr0vksni1Et9Dqd8wFqG9uZ/9AWGlpDlucMK/ZlLSXrVCVQUd0QBKE/kc+62l16el0WCot4rLtAeyjKvDVvJF9PHFnGkhlVfO2QUgJet3jdhD5B53wAiN0EQpGo5TniRRYEQbAmn3W1u8i63L8Rj3UXSMRZJ0joUge8bvG6CX2GzuMUulaSW7zIgiAI2cl3Xe0usi73X8Sw7gKJOOvO2zJS6ljoS8g4FQRBKCyyrgoHioSCdAHZlhH6AzJOBUEQCousq8KBMmANa6XUWcCdgAv4pdb6lu58X2JbRhD6MjJOBUEQCousq8KBMCBDQZRSLuAe4FtAFfBdpVRV7/ZKEARBEARBGMgMSMMamAJ8qLX+WGsdAh4DZvZynwRBEARBEIQBzEANBTkc2JnyuhY4qZf6IgiCIAiMuvHpA/r8J7ec7VBPBEFwioHqsc6WVZBRC1QptUAptUUptaW+vr4HuiUI+SFjVegPyDgV+gsyVgWnGKge61pgZMrrSuCLzh/SWq8CVgFMnjw5w/AWhL6CjFWhPyDjtLAcqIe7r9GXPe4yVgWnUFoPvPGklHID7wOnA58DbwAXa63/ZnNOPfBp/OUwYLfT/SwA/aGf/aGP0PV+7tZan+V0Z+zoNFYPJvrLWHKafjFWU8Zpf/x/kz73DMOA9/rRmtof/8b5cjBdK3Tteru0pg5IwxpAKfVPwM+Jye09oLW++QDO3aK1nuxY5wpEf+hnf+gj9J9+HszI/1GM/vZ36G/9BelzT9Hf+tzf+tsdDqZrhcJe70ANBUFr/QzwTG/3QxAEQRAEQTg4GKjJi4IgCIIgCILQo4hhnZ1Vvd2BLtIf+tkf+gj9p58HM/J/FKO//R36W39B+txT9Lc+97f+doeD6VqhgNc7YGOsBUEQBEEQBKEnEY+1IAiCIAiCIBQAMawFQRAEQRAEoQCIYS0IgiAIgiAIBUAMa0EQBEEQBEEoAGJYC4IgCIIgCEIBEMNaEARBEARBEAqAGNaCIAiCIAiCUADEsBYEQRAEQRCEAiCGtSAIgiAIgiAUADGsBUEQBEEQBKEAiGEtCIIgCIIgCAVADGtBEARBEARBKABiWAuCIAiCIAhCARDDWhAEQRAEQRAKgBjWgiAIgiAIglAAxLCOc9ZZZ2lAfuQn10+vI2NVfrr406vIOJWfLv70OjJW5aeLP11CDOs4u3fv7u0uCEKXkLEq9AdknAr9BRmrQiERw1oQBEEQBEEQCoAY1oIgCIIgCIJQAMSwFgRBEARBEIQCIIa1IAiCIAiCIBQAd293wEmUUi5gC/C51npGb/TBNDUNrSFCkShet4uhxV4MQ1m+BySPKaVwKTAMI+28rny3IPRFIhGTupYg4aiJx2UwvMSH223/fN+T4zyf/gk9Q1fHwYGuuYUaSzJ2BEGAAW5YA9cA7wKDeqNx09Rs39XM/Ie2UNvYTmV5gPsunczYEaUAGe899L0pBCNm2rFls8bz4Gs7+ME/jmXsiNK0G4TVd4txLfRFIhGT93Y1s+jhmuSYXTGnmuNGlFoaID05zvPpn9AzdHUcHOiaW6ixJGNHGGiMuvHpA/r8J7ec7VBP+h8DdsYrpSqBs4Ff9lYfGlpDyUUcoLaxnfkPbaGhNZT1vU8b2jKO3bDpHWZVj0ye15XvFoS+SF1LMGl4QGzMLnq4hrqWoOU5PTnO8+mf0DN0dRwc6JpbqLEkY0cQhAQD1rAGfg5cD5hWH1BKLVBKbVFKbamvry94B0KRaHKhTVDb2E4oEs36XpHXlfXzZQFP8ryufLcw8HB6rPYE4aiZdcxGopZTtEfHeT79+//t3Xt4XFd97//3d89oJFkysazYabDs3BqSE3jsxBIcLi0nDTTl1gKPTQpYTYA21OaW5tAApf31pKenHEJ+acolsQ8u0OTnUEjslpMGCkkJhlJukUxsIOSegBXSOJYdiGVJo5n9/f2x94xnRjMjaTSSRqPP63n0eGbttfb+7j1rf2d5z541Umyu+ul0+8FMc269+pL6zuLTDDlVGlNTDqzN7HXAIXcfrFbP3T/t7n3u3rdq1aq6x5FKJujpai8q6+lqJ5VMlF12PJ0tW/+Z0Yl8u+msW5rPXPfV+dCSCMr22WSichqaz35eS3xSbK766XT7wUxzbr36kvrO4tMMOVUaU7Oe9S8Dfs/MHge+AFxkZrvmO4jujhQ7L+3LJ9zcPX3dHamyy07rXjap7JpN69kzeDDfbjrrFmlEqztb2dHfW9Rnd/T3srqztWKb+ezntcQn82O6/WCmObdefUl9R0RyzH3aP3++KJnZhcCfTjUrSF9fnw8MDNR9+5oVpOks+AGeq746H3IzJ2SyIckGnhVkJvE1sAXtq/Xup4tlVpAm6TvzSTm1AenLi2VNq682+6wgCy4IjFXLy1+1qLSsUv2ZrFukESWTAc9d0T51xQLz2c9riU/mx3T7QS05tx7Ud0QElsDA2t33AnsXOAwRERERaXL6nEpEREREpA40sBYRERERqQMNrEVERERE6kADaxERERGROtDAWkRERESkDjSwFhERERGpAw2sRURERETqQANrEREREZE60MBaRERERKQONLAWEREREakDDaxFREREROpAA2sRERERkTrQwFqu6anrAAAgAElEQVREREREpA40sBYRERERqQMNrEVERERE6kADaxERERGROtDAWkRERESkDjSwFhERERGpAw2sRURERETqQANrEREREZE60MBaRERERKQONLAWEREREakDDaxFREREROqgKQfWZtZmZj8ws/1m9hMz+6uFjklEREREmltyoQOYI+PARe5+zMxagG+b2b+6+/fmYmNh6BweGWdsIkvCjLaWgPGMM5ENaQmMZCKIHicCEgGMToRkQ6clEdCatBPPA8MMsk7czhifCMEgaUYYby8TOtnQSQZGSyLADBIBTGSciXhZKhGQShoTWWc8E5IIjFQiIGEwmgnzdVoSRjob0poMGJsIyYROWzIgdEhnQ5KBEQTgbgQG45loP1oSFq3XIBFE+5eJ9ykZWLS/yejxaDpLKpmguyNFEBhh6AyPpElnsrQkAjLZkIw7bS0JVranODo6QTpzog3A8EiaMAzJOrh70fpm87rl4jAzEgZBEMx6vUtBJhNy6Nh4vl+v7mwlmZz6/+mFx3y6r+HYWIbh0TSZuM93t6doa6ueuiYmshw6Np5vs7qzlZaWxJTx1bKtRm7TTEr7Tld7S1GuOKk1wdMjJ47PstaAbBbSmSg3tacS+cfJwDipPeCXoyeet7UEZLIncmhLIqCtxchknJATua+9xUhnnEwY/UW51XCHsUyYX5d7tO2JfJ0AdycIgnzsYRjm83kQGO2pgJNaUxwZTRe/n0ycyJEnd7ROOz9NdcxKnyv3icxeU2Zld3fgWPy0Jf7zudhWGDoPPPUsl988wNDRUS4+bzXvvehstt2yj6Gjo/R0tXPt5vV87KsP8PSxcW7cspFP3f0Qd953iIvPW817LjqbdxXUve5NG/jMtx/lilecjWN84usP8t6Lzib0KPzj6SxX7T6Qr3/9JRvoWdnOM6NZDj87XrRs+5ZePnn3g9x536F83ZOWtfCOfxjI19nR38tjT/+K01c9h227BlnV2coHXnVO0Xqu2bSem77zGG9/2Rn5/di+ZSN37H+CV69/LqNlYvrIV+7n6WPjRfu+89I+zl7VyUNPH+PymwfKbmtHfy+f+PqJmG9+x4sYz4Rcf9cDXPbSM/jgnhN1d17axzmnLK/pjaD0dSvczyt/+5ya17sUZDIh9z/1LFt3DRa9bueesrzq4LrcMZ/qNRwby/DQ8AjbCra1vb+Xs7s7Kg4qJyay3H/o2KQ2567urDq4rmVbjdymmZTLs+97xfPyffDi81bz3lc8r+j47Ojvpa0l4G2fu4eXntlN/0tOK8q12/t7GXzsMFffcT8Xn7eaq1517qQcuqO/l47WgF+NZrj69vt4+tg4//D2F/LL0Qmu+MK9RTl+WSqRr7O9v5eT2pO8def3i+p0tia5Y/8T/O75PXzi6w9OymnXX7KBro4J3va5e/Jlhe8ZM8l7Ux2zcvl2NjlVRCJNeSsIgJklzOxe4BBwl7t/fy62MzySzicugE29a/ODaoCho6NctfsAWy88i6Gjo7zrln1s6l2br/uukrrvv20/m3rXcujZNFt3DbKpdy2Hj6U5MjLBkZGJfNLP1b/y1v1ksjB0ZHTSsm23DOa3lav7xNGxojpbdw1ywWnd+TekrReeNWk9H9xzgE29a4v2Y9st+9jct46jFWLK1Stsc/nNAxw6Np4/XuW2ldvn3POfDR/n8psH2NS7Nv8GlFt2+c0DDI+k6/K6Fe7nbNa7FBw6Np5/c4YTr9uhY+NV25U75lMd6+HRdL5v5tps2zXI8GjlNoeOjZdtM2V8NWyrkds0k3J5trAPbupdO+n4bN01yMEjo1E/e/mZk3Lttl2DXHTeqfn25XLo1l2DJIMER0Ym8nns4JHR/KA6V++q3QeK6mzbNUg645PqHD6WZnPfunyeK81pV966Px9zrqzwPWMmeW+qY1Yu3yr3icxe0w6s3T3r7ucDPcCLzOwFpXXM7J1mNmBmA08//XRN20lnsvlEBbCivaXoOUQJa0V7y6TH1eouSyWKHuf+ytXPuldclttW7vmyVGJy+/DEG0C1mEr3IxHYlNstfTyRDae1rZzC41CubjqTpRalr1vpfta63rlSj75aL4WvYc7Q0VEy2bBCi0ilY17tWGcK+mbRtsLKH0DV0mY+tzWf+zTf5qqfTpVnK+WHXL5LBFZ2ucefBBbm3NI6YZxfc3mpUr3COkNHRym96Jurk4tlqpgLy0rz+HTy00zfm2ay7mbQSDlVmkvTDqxz3P0ZYC/wqjLLPu3ufe7et2rVqprWn0om6Olqzz9/ZnSi6DlAT1c7z4xOTHpcre7xdLboce6vXP2EWcVluW3lnh9PZye3DyzftlpMpfuRDX3K7ZY+bkkE09pWTuFxKFc3lZz6vtlySl+30v2sdb1zpR59tV4KX8Ocnq52konq6aTSMa92rJMFfbNoW1U+qq6lzXxuaz73ab7NVT+dKs9Wyg+5fJcNvexyM8u3r5TLgji/5vJSpXqFdXq62in9P0+uTi6WqWIuLCvN49PJTzN9b5rJuptBI+VUaS5NObA2s1VmtiJ+3A68Erh/LrbV3ZFi56V9+YS1Z/Ag27dszD/P3Vu3Y+8j+fvl9gwezNe9saTudW/awJ7Bg6xenmJHfy97Bg9ycmeKlR0trOxo4drN64vqX3/JBpIJ6FnZPmnZ9i29+W3l6q7paiuqs6O/lx/+bJjt/b3R872PTFrPNZvWs2fwYNF+bN+ykd0DP6erQky5eoVtdl7ax+rO1vzxKret3D7nnp/WvYydl/axZ/Ag12wqrrvz0r78lxtn+7oV7uds1rsUrO5sZUfcX+DE67a6s7Vqu3LHfKpj3d2eyvfNXJvt/b10t1dus7qztWybKeOrYVuN3KaZlMuzhX1wz+DBScdnR38va1e2R/3sW49OyrXb+3u5+74n8+3L5dAd/b1kwiwrO1ryeWztynY+/ubzJ+X4wjrb+3tJJW1SnZM7U+we+Hk+z5XmtOsv2ZCPOVdW+J4xk7w31TErl2+V+0Rmz3IfhTUTM1sP3AQkiP7zcKu7/89qbfr6+nxgYKCm7Z2YFSSaJSM3K0gmnlWj3KwgYegkC2YFCeNvpk93VpAw/qZ5uVlBwvgb7blZQdKZkKBkVpBcnWqzgkxko9lECmcFSWdCkoWzggSQsGj/svE+1TYrSHTcFsGsIAt+iXA2fbVecrOCZLJRf9CsIA3ZZkH7ar376VzNCpKNc2lbKiBTkEOTJbOC5HJf4awgudk85mZWkIL3k4kTObIJZwVRTm1Ap3/oyzOq//hHXztHkTSUafXVpvw6ubsfAC6Yr+0FgbF6edt8bW7x6Sh+GgTGquWVrx6WW1atfq2mikMqSyYDnruifeqKJWo55m1tSdbMcOaLlpYEa7qWzahNrdtq5DbNpFzfKX2+JjWz49O5gGm72nlQr/eT6Rwz5UCR+mr4W0HM7Cwza40fX2hm78vd5iEiIiIi0igafmAN7AGyZvbrwGeAM4DPL2xIIiIiIiLFFsPAOnT3DPBG4O/c/Urg1AWOSURERESkyGIYWE+Y2VuAy4A74rKWKvVFRERERObdYhhYvx14CfA37v6YmZ0B7FrgmEREREREijT0V8zNLAF82N37c2Xu/hjw0YWLSkRERERksoa+Yu3uWWCVmWnGehERERFpaA19xTr2OPAfZnY7MJIrdPe/XbCIRERERERKLIaB9S/ivwBYvsCxiIiIiIiU1fADa3f/q4WOQURERERkKg0/sDazVcAHgOcD+d95dfeLFiwoEREREZESDf3lxdgtwP1Ev7j4V0T3XN+zkAGJiIiIiJRaDAPrbnf/DDDh7t9093cAL17ooERERERECjX8rSDARPzvk2b2WqIvMvYsYDwiIiIiIpMshoH1/zKzk4D3A58EngNcubAhiYiIiIgUa/iBtbvfET/8JfBbCxmLiIiIiEglDXuPtZl9zMy2lim/0syuWYiYREREREQqadiBNfA64NNlyj8OvHaeYxERERERqaqRB9bu7mGZwhCwBYhHRERERKSiRh5YHzezs0sL47LRBYhHRERERKSiRv7y4l8C/2pm/wsYjMv6gD8D/mTBohIRERERKaNhB9bu/q9m9gbgKuC9cfGPgU3u/qOFi0xEREREZLKGHVgDuPuPgcsAzKzT3Y8tcEgiIiIiImU18j3WAJjZS8zsPuC++PkGM7txgcMSERERESnS8ANr4O+A3wGGAdx9P/Dyag3MbK2ZfcPMfmpmPzGzK+YhThERERFZwhr6VpAcdz9oVjTDXnaKJhng/e6+z8yWA4Nmdpe731ePeMLQGR5JE4YhmdAJ3WlNBGQdJrIhicBoawnIZp2sQzobkgyMjtaA42nP12kJjFTSGE1H60kEhhm4QyoZMJF1MnHdwMDMCEMnEzrJREBgELoDVrTO9lbj2dFoncnA6GwNODYe5teddScZBCQTkMlCwsACIxlE6x/PRG1bEgGrO1tJJoOi/U5nsqSSCbo7UgSBZj5cisbGMgyPpvN9rLs9RVvb1Omklnbz1abR48tkQg4dG2ciG046N5tRGDpHR8fJZqPcOD4RMhHnyZbAsAAmMk42LmtLBYylC/JeW8DIWNQmmctvOGFIvk0QQG4C19ChJTDaUlG+/VVBDm1NBkyEIWEIVlC3o9UYGXey7kxkT8S2rNWK2re1BIxNhLSnAhxIT5x4HwgCCENoTyVY0d4cOVXvFbKULYaB9UEzeyngZpYC3gf8tFoDd38SeDJ+/KyZ/RRYQ3w7yWyEofPAU89y/V0PcNlLz+CDew6wqrOVD7zqHK7afYCho6P0dLXzube/kOPjWd79+X0MHR3l4vNW875XPI+tuwbzdW546wUkgqCo7JpN6/nWA0/xug1r2HbLvnz5dW/aQFtLwLs//8N82fWXbKCtJVFU79rN6zl5eSv/8eAhrr7jfnq62tne38sd9w7x8nNO4YN7TsS4o7+Xf4nLb/rOY7z/4ueRznjR+nb093LuKcsJAuOBp57l8psH8st2XtrHOfEyWTrGxjI8NDzCtoJ+u72/l7O7O6oODmtpN19tGj2+TCbk/qeeLcoVuXOzGQfXYeg8PjzCWCZLazLg+Hi2KC/d8NYLCMzyZReft5r3vuJ5k47pJ7/+IHfedyjfZmwi5P237S/Ktzd95zEue+kZ3PSdx3j7y87gtJOXMXxsomhdN27ZSCpp/O2dD+brXv6bZ7L6pDYOPzvOFV+4tygvr+hI8fbP3VMUy+Bjh+k742SCAN558+CkGN7+sjM45TltnN7dsahzau49Uu8VslQthoy8FXg30cB4CDg/fj4tZnY6cAHw/XoEMzyS5vKbB9jUuzY/SN164Vn5QTXA0NFRho6M5gfVAJt61+bfFHN1joxMTCr74J4DbO5bl3/DyJW//7b9HBmZKCq78tb9HD6WLiq7avcBho6MctF5p+bLtu0aZHPfuny8ufKtBeWbeteSCBKTtrt11yCHjo3n97tw2eU3DzA8kq7HYZVFZHg0nR90wIk+NjxavS/U0m6+2jR6fIeOjU/KFblzsxkNj6T52fBxnvrlOO42KS8dGZkoKtvUu7bsMd3Uu7aoTW5QnSvL5b7cv1ftPkA2y6R1veuWfSSDRFHdK2/dz0TG84PqXN0rb93P0JHRSbFcdN6pbN01yFO/HC8bw1W7D/Cz4eOLPqfqvUKWuoa/Yu3uh4EttbQ1s05gD/An7v6rMsvfCbwTYN26ddNaZzqTZejoKCvaW/KJo/BxzrJUoqhsOnUgSkKJwMqWL0slpl3m7tNaZ658RXsLgVG2TiYb4u5ll6UzU92VI/VQS1+dK5mwfF/IhF6hRe3t5qtNo8c3kQ0rnpuNpF79NJ3J5nNbubw0nfyay2uV2hTWKfw3WyHXBcakupVyZrm8nMuh5Zbl1rcslVj0OTX3HlmoEd8rGimnSnNp+CvWZvaJMn9/bWavn6JdC9Gg+hZ3/6dyddz90+7e5+59q1atmlY8qWSCnq52nhmdoKerHaDocc7xdLaobDp1AHq62smGXrb8eDo77bLCe9KrrTNX/szoBKFTtk4yEeT3u3RZKln8JiFzo5a+OleSgZXvJ1N8zFtLu/lq0+jxtSSCiudmI6lXP00lExxPZzmezpbNS9PJr7m8VqlNYZ3CfxNW/vUJnUl1K+XMcnnZ4vWWW5Zb3/F0dtHn1MXyXtFIOVWaS2Nl5fLaiG7/eCj+Ww+sBP7QzP6uXAOLRpWfAX7q7n9bz2C6O1LsvLSPPYMHuWbT+uhex72PcO3m9flk0tPVTs/Kdm5468Z82Z7Bg+zo7y2qs7KjZVLZNZvWs3vg52zfsrGo/Lo3bWBlR0tR2fWXbODkzlRR2bWb19Ozsp2773syX7a9v5fdAz/Px5sr31FQvmfwINkwO2m7O/p7Wd3Zmt/vwmU7L+2juyNVz8Mri0B3e4rtJf12e38v3e3V+0It7earTaPHt7qzdVKuyJ2bzai7I8Vp3cs45aRWzHxSXlrZ0VJUtmfwYNljumfwYFGb6960YVK+zeXyPYMHuXbzehIJJq3rxi0byYTZorrXX7KBlqTx8TefPykv96xsnxTL3fc9yY7+Xk45qbVsDNduXs9p3csWfU7Ve4UsdVZ4y0AjMrO7gYvdPRM/TwJ3Ar8N/MjdzyvT5jeAfwd+BOQ+K/2wu3+l0nb6+vp8YGBgWjHNdFaQXFluVpBMNiSoMCtIEH/jPD8rSBiSsKlnBSlc5/RnBTEyWS87K0g23oZmBZlkwXd4Jn11rjTjrBuNHl9uVpBMNpx0blawoH11tv30xKwgkAioPCuIOwmb4awgcZvcrCBmkJ3mrCBBQd3CWUEyWc/nYM0KMqP3igXf4UbIqY3m9A99eUb1H//oa+cokoYyrb7a8PdYE31psQP4Zfy8A3iuu2fNrOw3d9z928zhyRoExqrltV0pWrFscllXxywDKuM5bcXPTyqz3ZmazX5Lc2lrS7JmGgPVerSbrzbzua1a2iSTAc9d0T51xSYRBEZ3R9vUFQuV5NKTZnG4lk9z050V6k23fTPSe4UsZYthYP0x4F4z20s0WH458BEz6wD+bSEDExERERHJafiBtbt/xsy+AryIaGD9YXf/Rbz4qoWLTERERETkhMXw5UWAMaIffDkC/LqZVf1JcxERERGR+dbwV6zN7I+AK4Ae4F7gxcB3gYsWMi4RERERkUKL4Yr1FcALgZ+5+28R/Yri0wsbkoiIiIhIscUwsB5z9zEAM2t19/uBcxY4JhERERGRIg1/KwgwZGYrgC8Bd5nZUeAXU7QRERERWRQ0b3TzaPiBtbu/MX54tZl9AzgJ+OoChiQiIiIiMklDD6zNLAAOuPsLANz9mwsckoiIiIhIWQ19j7W7h8B+M1u30LGIiIiIiFTT0FesY6cCPzGzHwAjuUJ3/72FC0lEREREpNhiGFj/1UIHICIiIiIylYYfWOu+ahERERFZDBr6HmsAM3uxmd1jZsfMLG1mWTP71ULHJSIiIiJSqOEH1sCngLcADwHtwB/FZSIiIiIiDaPhbwUBcPeHzSzh7lngc2b2nYWOSURERESk0GIYWB83sxTRtHsfA54EOhY4JhERERGRIovhVpA/IIrz3UTT7fUAmxY0IhERERGREg17xdrMXg/0uPsN8fNvAqsBB74LPLyA4YmIiIiIFGnkK9YfAG4veN4K9AIXAtsWIiARERERkUoa9oo1kHL3gwXPv+3uR4AjZqZ7rEVERESkoTTyFeuuwifu/p6Cp6vmORYRERERkaoaeWD9fTO7vLTQzP4Y+MECxCMiIiIiUlEj3wpyJfAlM3srsC8u6yW61/oNCxaViIiIiEgZDTuwdvdDwEvN7CLg+XHxl9397um0N7PPAq8DDrn7C2YTSxg6h0fGGZvIkjBjeXuC0fGQidDJhk5LwkiaMZoJSQRGeyogm3GyDulsSDIwkoER4gRYvl2+3J3QwQzcoSVhZLJOayrAQ5jIOhPZkCAw2pIBE6EzkSl4nnVCd1LJBN0dKYLAZrO7ssRkMiGHjo0zkQ1pSQSs7mwlmaz+YdbYWIbh0TSZuB93t6doa5s6ndTSbr7a1NouDJ3hkTTpTFbnYA0K82tgRntLQDbrhEAmdFIJYyLrZN1pTQSEcV5tTQaEYVSeMCOIc6k7+TIzACOVMMYzYf51TQbGWCbKzalkQCKA0fSJ5W2pgLF0SDZ02pIBGYeJbEhbMsCB8TjXtyYDMsq/IlKgYQfWOfFAelqD6RL/QPTT5zfPZvth6Dzw1LNcfvMAQ0dH+ePfPJ3NL1zH4WfHuWr3AYaOjtLT1c71l2zgI1+5n1XLU/zp75zDyHiW9/7jD/PLb3jrBQRmHBvPTGrXkgy48RsPc9lLz+Cm7zzGey86mzv2P8HmvrWMZ5ytuwbz9bdv2cgn736IO+87xMXnreY9F53Nu27Zl1++89I+zjlluZK7TEsmE3L/U88W9bEd/b2ce8ryioPrsbEMDw2PsK2wX/b3cnZ3R9VBaC3t5qtNre1K84POwZkpd/w++7Y+JjIhvxrLsPf+p3jdhjVsu2Ufqzpb+YvX/Reu+MK9rOps5QOvOqcol97w1gsYmwh5/23782XXbFqfz6m5vNnT1c61m9fzsa8+wNPHxtm+ZSPtqQRv+9w9Ra/7HfcO8YPHn8lvZ1VnKx9+zblceeuJ9d+4ZSOfKlivXnsRaeR7rGfF3b8FHJnteoZH0vmkD7C5bx1DR0bzCR1g6OgoV966n60XnsWm3rU8cXQsP6jOLT8yMsHhY+my7Y6OTLCpdy0f3HOATb1r2XbLvmg7R8fyA55c/W237GNT71oANvWuzQ+qc8svv3mA4ZH0bHdblohDx8Yn9bGtuwY5dGy8Ypvh0XR+8Jlrs23XIMOj1ftdLe3mq03N2yrJDzoHZ6bc8Xvi6BiHno1y5ea+dWyLc9zWC8/iii/cm39cmkuPjEzkB9W5ssKcmsubQ0ej/L31wrPyOfXgkdFJr/vmvnVF29l64Vn5QXWu3rtK1qvXXkQa/or1XDKzdwLvBFi3bl3ZOulMNp9IARKBsSyVKCqDKKmuaG8pel5oWSpRtnzo6CjLUgmWkcivY+jo6LS2k6tbujydyU6577K4TKev1mIiG5btQ5lsWLFNJvTybUKvuq1a2s1Xm1rbleaHXJuleg7OtJ+WO36FuTIRWH55Yb4rl/uq5cty+Tn3PJeDS9slAptym+XWu1Rf+8VmrnKqSNNesZ4Od/+0u/e5e9+qVeVn8EslE/R0teefZ0PneDpbVAbQ09XOM6MTPDM6UXb58XS2Yrvj6SzPjE7k19HT1T7ldoB83dLlqWTxm4QsftPpq7VoSQRl+1AyUTk1JAMr32aKj79raTdfbWptV5ofcm2W6jk4035a7vgV5sps6PnlhfmuXO6rli8L82Zhee7x8XR2Urts6FNus9x6l+prv9jMVU4VWdID6+no7kix89K+fELdPfBzelZG9+jlynL3Su/Y+wh7Bg+ypquNT77lgqLlKztaOLkzVbZdV0cLewYPcs2m9ewZPMj2LRuj7XS1saO/t6j+9i0b2TMY/W7OnsGD3LhlY9HynZf20d2RmtdjJIvX6s7WSX1sR38vqztbK7bpbk+xvbRf9vfS3V6939XSbr7a1Lytkvygc3Bmyh2/NV1trF4e5crdAz9ne5zjdux9hI+/+fz849JcurKjhevetKGorDCn5vJm7h7rHXsfyefUtSvbJ73uuwd+XrSdHXsf4fpLitd/Y8l69dqLiLlX/3h0MTOz04E7pjMrSF9fnw8MDJRdduJb6yEJo2hWkDB0kvGsIGPxTB2Fs4JMZKNvj5fOChKGXlQehhAYhJVmBQlDAiuYFSRb8FzfSp9PC35wq/XVWuRmBclkQ5KaFaSZZgVZ0CCm209rmRVkIhuSimcFCd0J4llBPJ5hKT9TiIEXzAqSLci7uZk9apkVJB3nes0KUhcLfsDqnVNrcfqHvjyj+o9/9LVzFEmk0eJpENPqq017j7WZ/SNwIXCymQ0B/8PdP1PLuoLAWL28rajsOW0VKossMslkwHNXtE9dsUBbW5I10xio1qPdfLWptV0QGKuWV77CL9WVy68LomOK5yIi09C0A2t3f8tCxyAiIiIiS4fusRYRERERqQMNrEVERERE6kADaxERERGROtDAWkRERESkDjSwFhERERGpg6adFUREREREGk8zz5OtK9YiIiIiInWggbWIiIiISB1oYC0iIiIiUgcaWIuIiIiI1IEG1iIiIiIidaCBtYiIiIhIHWhgLSIiIiJSBxpYi4iIiIjUgQbWIiIiIiJ1oIG1iIiIiEgdaGAtIiIiIlIHGliLiIiIiNSBBtYiIiIiInWggbWIiIiISB1oYC0iIiIiUgcaWIuIiIiI1IEG1iIiIiIidZBc6ADmipm9Cvg4kAD+3t0/usAhiYiIyCJ1+oe+PKP6j3/0tXMUiTSyphxYm1kCuAH4bWAIuMfMbnf3+2pZXxg6vxpLMzKepSVpTGScTOgkA6OzLSCdgfFMSBg6icAIDEKHlsAYy4YkzGhJGBPZE+2WpQKOp0McSCUDkoExms7SkgxIJYyR8SxZd9paEpzc0UoQWB2PkDSrTCbk0LFxJrIhLYmA1Z2tJJPVP5gKQ2d4JE06kyWVTNDdkZqyv42NZRgeTef7c3d7ira2qdNJLe3mqw3UdixqaSOVj9v4eIbDx9Nk3UlYlE8DMzJhlD9bEkZghgFZd1KJgPFMmH+tgwDco3bjmZBUIsDixy2B0dmeYCztjGWyLGtJFLVtawk4Np4tOncKz6n2lgQAE9mw5te6Wn9RXxJZ/JpyYA28CHjY3R8FMLMvAK8HZjywDkPniWeOc/T4BF/e/wSv3bCGd92yj6Gjo/R0tfO5t7+QZ0bSXHnr/nzZNZvWc9N3HuPtLzuDj331AVYtT/Gei84uare9v5c77h3i//z74/R0tfKZ0OQAABUHSURBVHPt5vUV6+68tI9zTlmuBCtVZTIh9z/1LFt3Deb7zo7+Xs49ZXnFwXUYOg889SyX3zww7f42NpbhoeERthVsZ3t/L2d3d1QdvNbSbr7a1HosamkjlY/bGV3LJr12171pA20tAe/+/A/zZR9/8/nxBYoEwxMh2wryZWn+ffrYONdfsoGPfOV+Vi1P8d5XPI9tuwZ56Znd9L/ktKJce+OWjez67s/4zqPD7Ojv5XmrOnjw6RG27hpkVWcrH3jVOVy1+0DNr3W1/gKoL4k0gWa9x3oNcLDg+VBcNmPDI2nGM867btnH5r51+SQMMHR0lKEjo/lBda7sg3sOsKl3LVftPsDWC89iU+/aSe227Rpkc9+6/PNqdS+/eYDhkXRtR0KWjEPHxvODaoj6ztZdgxw6Nl6xzfBIOv9GnmszVX8bHk3nBz65Ntt2DTI8Wr2P1tJuvtpAjceihjZS5biVee3ef9t+joxMFJVd8YV7OTIygVmQH1TnlpXm36GjUY7O5dfc+i9/+ZmTcu27btnH5S8/M3/uPD2Szp9TWy88Kz+oLop5Bq91tf6iviTSHJr1inW5/977pEpm7wTeCbBu3bqyK0pnsgQWJblEYPmkl7MslZhUNnR0lBXtLfl/c2WldRIFVyGmqpvOZMvGJ0vDdPrqRDYs23cy2bDietOZ7Iz7Wyb08tsJJ51is243X22gtmNRS5tmNp1+CpWPW6XXblkqUbYsl5tLl5XLv6X5tVw+L8zLpfHk1llafyav9VT9RX1p/ky3r4rMVLNesR4C1hY87wF+UVrJ3T/t7n3u3rdq1aqyK0olE4QOPV3tZEOnp6u9aPnxdHZSWU9XO8+MTuT/zT0urZMteKOfqm4qWfzGIkvLdPpqSyIo23eSicqneSqZmHF/SwZWfjtTfFxdS7v5agO1HYta2jSz6fRTqHzcKr12x9PZsmW53Fy6rDD/FpYV5tdy+bwwL5fGU4/cXK2/qC/Nr+n2VZGZataB9T3A2WZ2hpmlgDcDt9eyou6OFK1J48YtG9k98HNu3LIxn/x6utrpWdnO9ZdsKCq7ZtN69gwe5NrN69mx9xH2DB6c1G57fy+7B36ef16t7s5L++juSM3uiEjTW93Zyo7+3qK+s6O/l9WdrRXbdHek2Hlp34z6W3d7iu0l29ne30t3e/U+Wku7+WoDNR6LGtpIleNW5rW77k0bWNnRUlT28Tefz8qOFtxDtpfky9L829MV5ehcfs2tf+e3Hp2Ua2/cspGd33o0f+6s6kjlz6kdex/h2s3rZ/VaV+sv6ksizcHcq388uliZ2WuAvyOabu+z7v431er39fX5wMBA2WWzmRVkPBsSFMwKko3rTG9WEGhrCTQrSGNZ8BeiWl/NzWCQyYYkNSvIUp8VZEGDqNZPYepZQUJ3Aotm+QiIZgXJhk6ywqwgudxaOCtIOhPNjjOTWUFGxrNF507hOdWmWUHmwoLv4FR9NWcup9trtKn85jqeRtvfaZpWX23We6xx968AX6nHuoLAWLGslRXL6rG2E7o6SgoKntd7W7I0JJMBz13RPnXFAkFgrFpe+ap2OW1tSdZMY6Baj3bz1QZqOxa1tJHKx621Ncma1rl9a3pOW+Vl3Z3Fz2s5p6qp1l/Ul0QWv2a9FUREREREZF5pYC0iIiIiUgcaWIuIiIiI1IEG1iIiIiIiddC0X14UERERkaVnIWcdadrp9mbKzJ4GfhY/PRk4vIDhTNdiiHMxxAjTj/Owu79qroOppqSvLiWLpS/NtUXRVwv66WJ83RTz/DgZuH8R5dTFeIxrtZT2Faa3v9PKqRpYl2FmA+7et9BxTGUxxLkYYoTFE+dSptcostiOw2KLFxTzfFlsMS+2eGdjKe0r1Hd/dY+1iIiIiEgdaGAtIiIiIlIHGliX9+mFDmCaFkOciyFGWDxxLmV6jSKL7TgstnhBMc+XxRbzYot3NpbSvkId91f3WIuIiIiI1IGuWIuIiIiI1IEG1iXM7FVm9oCZPWxmH5qjbaw1s2+Y2U/N7CdmdkVcfrWZPWFm98Z/rylo82dxTA+Y2e9MFa+ZnWFm3zezh8zsi2aWistb4+cPx8tPrxLn42b2oziWgbhspZndFa/3LjPrisvNzD4Rr/eAmW0sWM9lcf2HzOyygvLeeP0Px22t2jYqxHhOwfG618x+ZWZ/0mjHUmanXF9cCszss2Z2yMx+XFA27fNjoc1HPp1mHJVybt3y2RzGnjCzH5rZHfHzGeejSjlvjuJdYWa7zez++Hi/ZDEc52oapR/Ph0rnSjMrPcdmzd31F/8BCeAR4EwgBewHzpuD7ZwKbIwfLwceBM4Drgb+tEz98+JYWoEz4hgT1eIFbgXeHD/eAWyLH78L2BE/fjPwxSpxPg6cXFL2MeBD8eMPAdfEj18D/CtgwIuB78flK4FH43+74sdd8bIfAC+J2/wr8Opq25jm6/efwGmNdiz1N+tzZlJfXAp/wMuBjcCPC8pqOj8WIPZ5yafTjKVSzq1bPpvD2P878Hngjvj5jPJRpZw3h/HeBPxR/DgFrFgMx3kx9ON52t+y58pCxzXH+1x0js32T1esi70IeNjdH3X3NPAF4PX13oi7P+nu++LHzwI/BdZUafJ64AvuPu7ujwEPx7GWjTe+8nsRsDtufxPwhoJ13RQ/3g28Iq4/XYXtS9d7s0e+B6wws1OB3wHucvcj7n4UuAt4VbzsOe7+XY969s0VYizcxlReATzi7tUm+m+kYylSlbt/CzhSUlzr+THf5iWfTkeVnFuXfDZXcZtZD/Ba4O/j57Xko0o5by7ifQ7RfwY/A+DuaXd/hgY/zlNomH48H2oYnyxqpedYPWhgXWwNcLDg+RBz3KHij+suAL4fF70n/kjsswUf8VaKq1J5N/CMu2dKyovWFS//ZVy/HAfuNLNBM3tnXHaKuz8Zt38SWF1jjGvix6Xl1bYxlTcD/1jwvJGOpcxOub64VNV6fsy3ec+n01GSc+uVz+bK3wEfAML4eS35aD5jPhN4Gvhc/NH635tZB41/nKtppFjmVZnxSTMqPcdmTQPrYuWuNs7ZtClm1gnsAf7E3X8FbAfOAs4HngSumyKumZZXW1c5L3P3jcCrgXeb2csr1Kt3jDMW32f4e8BtcVGjHUuZnZn0RWkMDXd+lMm5FauWKat73qrGzF4HHHL3wWnEVW3ZfL4OSaJbl7a7+wXACNGtH5U0QsxTaaRY5s0MzpVFq8I5NmsaWBcbAtYWPO8BfjEXGzKzFqJOe4u7/xOAuz/l7ll3D4GdnPi4rlJclcoPE32kliyzH/k28fKTmPxRM3E8v4j/PQT8cxzPU/FHdcT/HqoxxqH4cWk5VbZRzauBfe7+VBxzQx1LmZ0KfXGpquX8WAjzlk+no1zOpX75bC68DPg9M3uc6PaDi4iurs00H81nzEPAkLvnrnDuJhpoN/JxnkojxTIvKpwrzWjSOWZmu2a7Ug2si90DnB1/6zpFdGvB7fXeSHzf22eAn7r73xaUn1pQ7Y1AbiaA24E3x9/6PgM4m+iLf2Xjje9Z/gawOW5/GfB/C9aV+4b1ZuDuuH5pjB1mtjz3GLg4jqewfel6L42/5f1i4JfxR35fAy42s674doyLga/Fy541sxfHx+PSCjEWbqOat1BwG0gjHUuZnSp9camq5fxYCPOST6ejUs6lTvlsLmJ29z9z9x53P53o2N3t7luYeT6qlPPmIub/BA6a2Tlx0SuA+2jg4zwNDdOP50OVc6XpVDjH+uuxYv0Vfzv0NUTfgn0E+PM52sZvEH2UdAC4N/57DfD/AT+Ky28HTi1o8+dxTA8Qz55RLV6ie91+QPRFlduA1ri8LX7+cLz8zAoxnkn07ef9wE9y6ya6Z+/rwEPxvyvjcgNuiOP4EdBXsK53xNt7GHh7QXkf0QDpEeBTnPjBorLbqHI8lwHDwEkFZQ1zLPU36/OlbF9cCn9E/1l8EpggunL2hzM9PxY4/jnPp9OMo1LOrVs+m+P4L+TErCAzzkeVct4cxXo+MBAf6y8RzeqxKI5zo/fjedrXsufKQsc1D/udP8dm+6dfXhQRERERqQPdCiIiIiIiUgcaWIuIiIiI1IEG1iIiIiIidaCBtYiIiIhIHWhgLSIiIiJSBxpYNwEz+3Mz+0n88933mtl/rVL3H8xsc6XlBXUei9e1z8xeUqHeVjO7dLbxS/Mxsx4z+79m9pCZPWJmH4/ngJ3LbR6L/z3dzH5cUP4bZvYDM7vfzB4ws3fXYzvSnMzsFDP7vJk9amaDZvZdM3tjmXpF/ayg/H+a2SunsZ0LzMzN7HfqFbs0r+n2y3mM59VmNmBmP41z6/+7ULE0Gg2sF7l40Ps6YKO7rwdeCRysw6qvcvfziX6O9v+U2W7S3Xe4+8112JY0kfgHBv4J+JK7nw08D+gE/maW601OXWtSm18DPg9sdfdziX5p6x0L+YYkjSvuu18CvuXuZ7p7L9EPR/SU1KvYF939L93936axubcA347/LRuLmek9WqbdL6u0T9Q5nhcQ/fZEv7v/F+AFwKMzaD/jXL6Y6KRd/E4FDrv7OIC7H3b3X5jZX5rZPWb2YzP7dHxiFjGzXjP7Zvy/36+V/FphzreAX4/r7zWzj5jZN4ErzOxqM/vTeNmvm9m/mdn++Cr3WXH5VXEcB8zsr+bqIEhDuQgYc/fPAbh7FriSaEB7j5k9P1cx7lO9Fv264mfj5T80s9fHy99mZreZ2b8Ad5pZp5l9Pe5jP8rVq+LdwD+4+744lsPAB4Cr4vUXfYJTcNV7ptuR5nARkHb3HbkCd/+Zu3+ytC9WWkGuT8VX9G4tKL8wbpsbKG0G3kb0C4Ntcfnp8RXAG4F9wFozuzi+Orkv3n5nXHfKHC9No1q/PN3M/j3uH/vM7KWQ72/fMLPPE/34Dmb2pfj9/idm9s7cuszsD83swTgf7zSzT8Xlq8xsT9zP7jGzl8VNPgD8jbvfH8eScfcb4za/a2bfj/P4v5nZKXH51XE/vRO42cyeb9EniffG44Oz5/wozhMNrBe/O4mS74NmdqOZ/be4/FPu/kJ3fwHQTnRVO8/MWoBPApvj//1+lvJXFH+X+KSMrXD3/+bu15XUuwW4wd03AC8FnjSzi4l+PvdFRL/G1WtmL5/V3spi8HxgsLDA3X8F/By4A7gE8j87/1x3HyT6Zbi73f2FwG8B11r08+UALwEuc/eLgDHgje6+Ma533RQDikmxEP0q3HlT7MNMtyPN4flEA9pKCvviVO4CXlzQj38f+GL8+GXAY+7+CLCX6Jf9cs4Bbnb3C4AR4C+AV8Z9cQD473G9qjlemkq1fnkI+O24f/w+8ImCZS8i+qXIXL57R/x+3we8z8y6zey5wP8DvBj4beDcgvYfB66P8/Im4O/j8hcwOa/mfBt4cdx/v0A0CM/pBV7v7m8FtgIfjz8Z7yP6Zdmm0NSX45cCdz9mZr3AbxINAL5oZh8CnjWzDxD93PdKop+C/peCpucQnRx3xeOFBNFPJ+dca2Z/ATxN9DPKOV+khJktB9a4+z/HMY3F5RcDFwM/jKt2Eg20vzWbfZaGZ0Q/iVuufC+wHfgfRAPs2+JlFwO/l/sEhOjnmdfFj+9y9yMF6/hI/B+0EFgDnAL85wxjmc4+zGQ70oTM7Aain3hOE/30dmFfrMrdM2b2VeB3zWw38FpODDLeQjToIP73D4hunwL4mbt/L378YqL/BP5HnKdTwHfjZb81RY6XJlXSL18JfMrMzgeyRLfe5fzA3R8reP4+O3Eb3Fqi9+NfA76Z69dmdlvBOl4JnFdwTeE58ft9NT1E45BTifpr4fZvd/fR+PF3gT83sx7gn9z9oWns+qKggXUTiD9q3wvsNbMfAX8MrAf63P2gmV1NNFApZMBP3L3sFxOJ7rHeXaZ8pExZpSt5Bvxvd590j7Y0tZ8QXd3IM7PnECXye4BhM1tPdHXlj3NVgE3u/kBJu/9KcZ/bAqwCet19wsweZ3LfLo2lD7i9oKyX6MofQIb4k7v4inTuC5Yz3Y40h6K+6+7vNrOTOdFfyuW/ar5IdDvSEeAed3/WovtdNxH9R/LPifp+d8GApXAbRjSYL7oPO7515Eaq53hpHtX65ZXAU8AGolw2VtAu35fM7EKigfJL3P24me0l6jPVPokL4vqjhYVm9hOiPLq/TJtPAn/r7rfH27y6XDzu/nkz+z7Rfzi/ZmZ/5O53V4ll0dCtIIucmZ1Tcm/S+UBucHI4vh+v3CwgDwCrLJ7xw8xarODe15mIP+YfMrM3xOtqNbNlwNeI7qvN3RO4xsxW17INWVS+DiyzeMaYeCBxHdG9zsc58fHgSe6eu83oa8B7c7dbmNkFFdZ9EnAoHuz+FnDaFLHcALwtvpqDmXUT3fL01/Hyx4neIABeD7TUuB1pDncDbWa2raBs2SzWtxfYCFzOiU/7Xgnsd/e17n66u58G7AHeUKb994CXmVnuey7LzOx5nBhEV8vx0jyq9cuTgCfdPST65KPSFxVPAo7Gg+pziT4NAfgB8N/MrMuiLxUWXhS5E3hP7kkujwLXAh+O+yJmFphZ7halk4An4seXVdohMzsTeNTdP0F04WN9pbqLjQbWi18ncJOZ3WdmB4g+Nrwa2El0b/SXiK4SFnH3NFEyvsbM9gP3Et0bXas/IPqY6QDwHeDX3P1OohkZvhtfSd8NTPUxkixy7u7AG4E3mdlDwINEV1E+HFfZTfSN9lsLmv010aD2gEVTmP015d0C9JnZANFV5funiOVJoB/4tJk9APwC+IS7fzOuspPoTeUHQOHV8RltR5pD3HffQNQnHov7xU3ABys0OcfMhgr+3lSyvizR9wpeHf8L0W0g/1yynj3AW8vE8zTRFxz/Mc6t3wPOdfdnmCLHS/OYol/eCFxmZt8juoWj0qcqXwWScT/6a6K+hLs/AXwE+D7wb8B9wC/jNu8jyoMHzOw+ovuicfcDwJ8Q9cufAj8mmkgBovHHbWb278DhKrv1+8CPzexeovu6m2aGMYteLxGR5mfRHNZbgZe7+9GFjkdEZKGZWWf8fa0k0X/6Ppv7zpTMnAbWIiIiIkuURT/u8kqiW4zuBK5wDQ5rpoG1iIiIiEgd6B5rEREREZE60MBaRERERKQONLAWEREREakDDaxFREREROpAA2sRERERkTrQwFpEREREpA7+fy6I1o7GlHY3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#多变量散点图\n",
    "sns.pairplot(df[['SalePrice', 'OverallQual', 'GrLivArea', 'GarageCars']])\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "你可以找出哪几个变量之间是正相关的吗？它们的相关性与之前的相关系数矩阵热图是否一致?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据清洗 \n",
    "上面我们完成了对数据的分析工作,接下来我们要开始清洗数据,以便为后续的模型训练做好准备工作,数据清洗需要完成以下一些工作:\n",
    "\n",
    "* 对目标变量和特征变量进行纠偏(对数化处理)\n",
    "* 对分类型变量进行one-hot编码\n",
    "* 用特征变量的均值来填充空值\n",
    "* 创建训练集和测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据清洗前的特征变量的数量为: 75\n",
      "数据清洗后的特征变量的数量为: 275\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:13: RuntimeWarning: invalid value encountered in log1p\n",
      "  del sys.path[0]\n"
     ]
    }
   ],
   "source": [
    "print(\"数据清洗前的特征变量的数量为:\",len(df.columns)-1)\n",
    "#对目标变量进行对数化纠偏\n",
    "df[\"SalePrice\"] = np.log1p(df[\"SalePrice\"])\n",
    "\n",
    "#对数值型特征变量进行对数化处理:1.过滤出数值型变量,2.计算偏度,3.对偏度大于0.75的数据进行对数化纠偏\n",
    "#1.过滤出数值型变量\n",
    "numeric_feats = df.dtypes[df.dtypes != \"object\"].index\n",
    "#2.计算偏度\n",
    "skewed_feats = df[numeric_feats].apply(lambda x: skew(x.dropna())) #compute skewness\n",
    "skewed_feats = skewed_feats[skewed_feats > 0.75]\n",
    "skewed_feats = skewed_feats.index\n",
    "#3.对偏度大于0.75的数据进行对数化纠偏\n",
    "df[skewed_feats] = np.log1p(df[skewed_feats])\n",
    "#4.对分类型变量进行one-hot编码,分类型变量会被横向展开为多个变量\n",
    "df = pd.get_dummies(df)\n",
    "#用均值填充空值\n",
    "df = df.fillna(df.mean())\n",
    "\n",
    "print(\"数据清洗后的特征变量的数量为:\",len(df.columns)-1)\n",
    "#创建训练集和测试集\n",
    "X, y = df.drop(['SalePrice'], axis = 1), df['SalePrice']\n",
    "X_train, X_test, y_train, y_test  = train_test_split(X, y, test_size = 0.2, random_state = 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "特征变量的数量,由原来的75个，变成了现在的275个，这是因为我们对分类型变量做了one-hot编码(pd.get_dummies)，经过这样处理以后,原来的分类型变量会被横向展开为多个变量,因此特征变量的总数会增加很多。偏度skew是指偏离正太分布的程度,对于正态分布数据，偏度应约为0.，偏度值> 0意味着数据分布呈现右偏,偏度值<0意味着数据分布呈现左偏。 在统计学上，函数skewtest可用于确定偏度值是否足够接近0(正太分布)。这里我们只对偏度值大于0.75的数据进行纠偏,偏度<0.75的数据是可以容忍的,现实中是不存在100%满足正太分布的数据。所以数据呈现轻微的偏斜是可以容忍的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 回归模型\n",
    "\n",
    "## <a href=\"https://scikit-learn.org/stable/modules/linear_model.html#elastic-net\">ElasticNet</a>(弹性网络)  \n",
    "* Ridge(岭回归)和Lasso(套索回归)都是常用的正则化的线性回归模型。它们分别使用L2和L1正则化。\n",
    "* ElasticNet是Ridge(岭回归)和Lasso(套索回归)混合体,它同时使用L2和L1正则化,这种组合允许学习稀疏模型，其中包含了较少的像Lasso回归一样的非零权重，同时仍然保持Ridge的正则化特性。\n",
    "* 当存在多个彼此相互关联的特征变量时ElasticNet非常有用。\n",
    "* Skearn的ElasticNetCV类可用于通过交叉验证设置参数alpha(α)和l1_ratio(ρ)。\n",
    "* ElasticNetCV：通过交叉验证选择最佳模型。  \n",
    "\n",
    "下面我们使用Skearn的<a href=\"https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNetCV.html\">ElasticNetCV</a>来预测一下我们的目标变量,看看它效果如何。首先我们要对模型进行训练,并拟合出最佳的参数alpha和l1_ratio。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最佳 alpha: 0.00013634\n",
      "最佳 l1_ratio: 0.700\n",
      "迭代次数 84\n"
     ]
    }
   ],
   "source": [
    "cv_model = ElasticNetCV(l1_ratio=[.1, .5, .7, .9, .95, .99, 1], eps=1e-3, n_alphas=100, fit_intercept=True, \n",
    "                        normalize=True, precompute='auto', max_iter=2000, tol=0.0001, cv=6, \n",
    "                        copy_X=True, verbose=0, n_jobs=-1, positive=False, random_state=0)\n",
    "               \n",
    "cv_model.fit(X_train, y_train)\n",
    "print('最佳 alpha: %.8f'%cv_model.alpha_)\n",
    "print('最佳 l1_ratio: %.3f'%cv_model.l1_ratio_)\n",
    "print('迭代次数 %d'%cv_model.n_iter_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面我们要在训练集和测试集上进行预测和评估，我们使用R^2和RMSE作为评估指标:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train r2 score:  0.9352316018794959\n",
      "Test r2 score:  0.8300355301028951\n",
      "Train RMSE: 0.0963\n",
      "Test RMSE: 0.1604\n"
     ]
    }
   ],
   "source": [
    "y_train_pred = cv_model.predict(X_train)\n",
    "y_pred = cv_model.predict(X_test)\n",
    "print('Train r2 score: ', r2_score(y_train_pred, y_train))\n",
    "print('Test r2 score: ', r2_score(y_test, y_pred))\n",
    "train_mse = mean_squared_error(y_train_pred, y_train)\n",
    "test_mse = mean_squared_error(y_pred, y_test)\n",
    "train_rmse = np.sqrt(train_mse)\n",
    "test_rmse = np.sqrt(test_mse)\n",
    "print('Train RMSE: %.4f' % train_rmse)\n",
    "print('Test RMSE: %.4f' % test_rmse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里的RMSE实际上是RMSLE（Root Mean Squared Logarithmic Error）,因为我们的目标变量已经被对数化处理了。 这是一篇很好的<a href=\"https://www.quora.com/What-is-the-difference-between-an-RMSE-and-RMSLE-logarithmic-error-and-does-a-high-RMSE-imply-low-RMSLE/\">文章</a>，解释了RMSE和RMSLE之间的区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 提取重要特征\n",
    "\n",
    "训练完ElasticNetCV后我们可以从中提取对模型来说最重要的特征,也就是特征变量权重最大和最小的变量,我们取最大,最小各30个特征变量:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_importance = pd.Series(index = X_train.columns, data = cv_model.coef_)\n",
    "n_selected_features = (feature_importance>0).sum()\n",
    "feature_importance.sort_values().tail(30).plot(kind = 'bar', figsize = (12,5));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们看到特征变量GrLivArea的权重最大,GrLivArea表示“房屋地面以上面积”,可见房屋面积越大,房价也越高，这符合常理。下面我们再来看看权重值最小的30个变量:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_importance.sort_values().head(30).plot(kind = 'bar', figsize = (12,5));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们看到特征变量Condition2_PosN的权重最小,Condition2是个分类型变量,其中PosN表示“靠近停车场”。这是否意味着停车场附近会有噪声从而影响房价?\n",
    "\n",
    "因为ElasticNet是Ridge(岭回归)和Lasso(套索回归)混合体,它同时使用L2和L1正则化,这种组合允许学习稀疏模型，那么我们看看有多少特征变量的权重为零,权重为零意味着这些特征对模型来说是无关紧要的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "162 个权重为零的特征, 所在比例为 of 58.91%\n"
     ]
    }
   ],
   "source": [
    "feature_importance = pd.Series(index = X_train.columns, data = np.abs(cv_model.coef_))\n",
    "zero_weight_features = (feature_importance==0).sum()\n",
    "print('{0:d} 个权重为零的特征, 所在比例为 of {1:2.2f}%'.format(\n",
    "    zero_weight_features,(zero_weight_features/len(feature_importance))*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可见有一半以上(58.91%)的特征对模型来说是无关紧要的,它们将被抛弃。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# XGBoost\n",
    "\n",
    "\n",
    "<a href=\"https://xgboost.readthedocs.io/en/latest/\">XGBoost</a>全名叫（eXtreme Gradient Boosting）极端梯度提升，经常被用在一些Kaggle竞赛中，其效果显著。它是大规模并行boosted tree的工具，它是目前最快最好的开源boosted tree工具包,大家可以参考这篇<a href=\"https://blog.csdn.net/huibeng7187/article/details/77588001\">博客</a>。\n",
    "\n",
    "下面我们创建基于4个不同参数的Xgboost模型,看看它们效果如何:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train r2 score:  0.9546691336034475\n",
      "Test r2 score:  0.8856612816972917\n",
      "Train RMSE: 0.0820\n",
      "Test RMSE: 0.1316\n"
     ]
    }
   ],
   "source": [
    "#使用默认参数\n",
    "xgb_model1 = XGBRegressor()\n",
    "xgb_model1.fit(X_train, y_train, verbose=False)\n",
    "\n",
    "y_train_pred1 = xgb_model1.predict(X_train)\n",
    "y_pred1 = xgb_model1.predict(X_test)\n",
    "\n",
    "print('Train r2 score: ', r2_score(y_train_pred1, y_train))\n",
    "print('Test r2 score: ', r2_score(y_test, y_pred1))\n",
    "train_mse1 = mean_squared_error(y_train_pred1, y_train)\n",
    "test_mse1 = mean_squared_error(y_pred1, y_test)\n",
    "train_rmse1 = np.sqrt(train_mse1)\n",
    "test_rmse1 = np.sqrt(test_mse1)\n",
    "print('Train RMSE: %.4f' % train_rmse1)\n",
    "print('Test RMSE: %.4f' % test_rmse1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train r2 score:  0.9678837547788781\n",
      "Test r2 score:  0.8931330796873692\n",
      "Train RMSE: 0.0699\n",
      "Test RMSE: 0.1272\n"
     ]
    }
   ],
   "source": [
    "xgb_model2 = XGBRegressor(n_estimators=1000)\n",
    "xgb_model2.fit(X_train, y_train, early_stopping_rounds=5, \n",
    "             eval_set=[(X_test, y_test)], verbose=False)\n",
    "y_train_pred2 = xgb_model2.predict(X_train)\n",
    "y_pred2 = xgb_model2.predict(X_test)\n",
    "\n",
    "print('Train r2 score: ', r2_score(y_train_pred2, y_train))\n",
    "print('Test r2 score: ', r2_score(y_test, y_pred2))\n",
    "train_mse2 = mean_squared_error(y_train_pred2, y_train)\n",
    "test_mse2 = mean_squared_error(y_pred2, y_test)\n",
    "train_rmse2 = np.sqrt(train_mse2)\n",
    "test_rmse2 = np.sqrt(test_mse2)\n",
    "print('Train RMSE: %.4f' % train_rmse2)\n",
    "print('Test RMSE: %.4f' % test_rmse2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train r2 score:  0.9479569687487649\n",
      "Test r2 score:  0.8840040768045745\n",
      "Train RMSE: 0.0869\n",
      "Test RMSE: 0.1325\n"
     ]
    }
   ],
   "source": [
    "xgb_model3 = XGBRegressor(n_estimators=1000, learning_rate=0.05)\n",
    "xgb_model3.fit(X_train, y_train, early_stopping_rounds=5, \n",
    "             eval_set=[(X_test, y_test)], verbose=False)\n",
    "y_train_pred3 = xgb_model3.predict(X_train)\n",
    "y_pred3 = xgb_model3.predict(X_test)\n",
    "\n",
    "print('Train r2 score: ', r2_score(y_train_pred3, y_train))\n",
    "print('Test r2 score: ', r2_score(y_test, y_pred3))\n",
    "train_mse3 = mean_squared_error(y_train_pred3, y_train)\n",
    "test_mse3 = mean_squared_error(y_pred3, y_test)\n",
    "train_rmse3 = np.sqrt(train_mse3)\n",
    "test_rmse3 = np.sqrt(test_mse3)\n",
    "print('Train RMSE: %.4f' % train_rmse3)\n",
    "print('Test RMSE: %.4f' % test_rmse3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train r2 score:  0.9869643143887125\n",
      "Test r2 score:  0.8940290084276306\n",
      "Train RMSE: 0.0448\n",
      "Test RMSE: 0.1267\n"
     ]
    }
   ],
   "source": [
    "xgb_model4 = XGBRegressor(n_estimators=100, learning_rate=0.08, gamma=0, subsample=0.75,\n",
    "                         colsample_bytree=1, max_depth=7, n_jobs=-1)\n",
    "xgb_model4.fit(X_train,y_train)\n",
    "y_train_pred4 = xgb_model4.predict(X_train)\n",
    "y_pred4 = xgb_model4.predict(X_test)\n",
    "\n",
    "print('Train r2 score: ', r2_score(y_train_pred4, y_train))\n",
    "print('Test r2 score: ', r2_score(y_test, y_pred4))\n",
    "train_mse4 = mean_squared_error(y_train_pred4, y_train)\n",
    "test_mse4 = mean_squared_error(y_pred4, y_test)\n",
    "train_rmse4 = np.sqrt(train_mse4)\n",
    "test_rmse4 = np.sqrt(test_mse4)\n",
    "print('Train RMSE: %.4f' % train_rmse4)\n",
    "print('Test RMSE: %.4f' % test_rmse4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以看到第四个模型在测试集上的R^2成绩最好。并且我们采样默认参数的第一个XGboost模型的表现都要优于ElasticNet。\n",
    "\n",
    "接下来我们查看一下最优模型xgb_model4 最重要的前30个特征变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "xgboost的特征数量: 201\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xb636f98>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "dic = xgb_model4.get_booster().get_fscore()\n",
    "feature_importance = pd.DataFrame.from_dict(dic,  orient='index', columns=['fscore'])\n",
    "print('xgboost的特征数量:',len(feature_importance))\n",
    "feature_importance_plot = feature_importance.sort_values(by=\"fscore\" , ascending=False)[:30]\n",
    "feature_importance_plot.plot(kind = 'bar', figsize = (12,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "XGboost的特征数量是201个，可见也有一部分不重要的特征被舍弃了，其中最重要的前5个特征变量是LotArea、LotFrontage、MSSubClass、BsmtUnSF、TotalBsmtSF,它们都不在ElasticNet的前5个重要特征中,看来xgboost的重要特征的认定方法和ElasticNet完全不一样。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面我们只取这201个特征，再用我们之前的最优模型xgb_model4再进行一下训练和预测，看看模型表现如何:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train r2 score:  0.986369497945745\n",
      "Test r2 score:  0.902652461231264\n",
      "Train RMSE: 0.0458\n",
      "Test RMSE: 0.1214\n"
     ]
    }
   ],
   "source": [
    "train_x=df[feature_importance.index]\n",
    "train_y=df['SalePrice']\n",
    "X_train, X_test, y_train, y_test  = train_test_split(train_x, train_y, test_size = 0.2, random_state = 0)\n",
    "\n",
    "xgb_model4.fit(X_train,y_train)\n",
    "y_train_pred4 = xgb_model4.predict(X_train)\n",
    "y_pred4 = xgb_model4.predict(X_test)\n",
    "\n",
    "print('Train r2 score: ', r2_score(y_train_pred4, y_train))\n",
    "print('Test r2 score: ', r2_score(y_test, y_pred4))\n",
    "train_mse4 = mean_squared_error(y_train_pred4, y_train)\n",
    "test_mse4 = mean_squared_error(y_pred4, y_test)\n",
    "train_rmse4 = np.sqrt(train_mse4)\n",
    "test_rmse4 = np.sqrt(test_mse4)\n",
    "print('Train RMSE: %.4f' % train_rmse4)\n",
    "print('Test RMSE: %.4f' % test_rmse4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
